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AMiner: search and mining of academic social networks Offering comprehensive search and mining services for academic community

The new CityIQ Knowledge Service integrates data on cities around the world and we have a huge city database as the basis for our CityIQ score. The amount of urban data that this database possesses is one of the largest in the world and integrates the differences in statistical standards between countries, while using advanced technologies and introducing advanced algorithms to keep data dynamic. We provide data query services: Users can view the historical scores of the cities assessed in the database and their respective sub-indicators. At the same time, the smart city evaluation can interact with the user, and the user can submit supplementary corrections for the index of a certain city. After the data review and data reliability verification, the score system can be included. The City IQ data could be shared to the people from every corner of the world freely.

This is to meet the requirements of students,engineers and researchers in Engineering Education. They can get the latest open online courses of the famous universities in the world, such as Tsinghua university,Stanford University, MIT and so on. Most of these courses are part of engineering disciplines.

To meet the requirements of engineers and researchers in Engineering Education. They can get the latest ideas of the world's leading experts in international engineering education.

Visualization Tool Kit for Big Data

Technology Trends

Online NLP Tool

In order to enhancing the computer skills of engineering trainees at home and abroad, training multi-level composite talent and promoting international development of engineering education, International Knowledge Centre for Engineering Sciences and Technology under the Auspices of UNESCO (IKCEST), International Centre for Engineering Education under the Auspices of UNESCO (ICEE) and XuetangX will jointly sponsor the 2018 Special Training on International Engineering Education—Frontier Computer Knowledge Workshop.

Provide Global Cultural Heritage Infomation

The Planning Education sector is committed to creating the world's best knowledge sharing platform in planning education field. At current stage, it mainly focuses on the sharing function of educational videos including related areas like planning education, smart city, urbanization, smart transport, AI aided planning, etc. The platform plans to introduce the latest AI technology, embed AI language translation module to achieve initial bilingual Chinese-English translation, relying on artificial intelligence translation technology, it gradually eliminate language barriers, so that learners can access the educational resources of all languages without barriers.

The vegetation degradation, drought and other environmental issues in the Mongolian Plateau have been as the hot spot in the study of the climate change and the ecological environment changes in Northeast Asia. Based on the NOAA AVHRR NDVI-PathFinder 10d remote sensing data of 1981-1999 and MODIS vegetation index and the surface temperature 16d data of 2000-2012, the knowledge service inverted Temperature and Drought Vegetation Index (TVDI) by the Ts-NDVI general space, their spatio-temporal distribution and changes were calculated. With the WebGIS technology, the application of Mongolian Plateau drought monitoring annual spatial distribution has been released. This application shows Mongolian Plateau drought monitoring annual spatial distribution from 1981 to 2012. MapServer is used to release Web Map Service (WMS) referring the international specification. The Combination of data and MapBox tiles has been used by OpenLayers to generate the map view. When the app page opened, the satellite image could be visualized as the map service. In the map operation on the right side of the app page, users can select different years to view the corresponding data map. Selecting GIS data operation in the sidebar navigation, users can see the corresponding option of year and click the drop-down arrow to display the year lists, including the years from 1981 to 2012. In the bottom right corner of the app page, users can see application-related documents and information which are classified by label control. The user can choose “more” to get more readings.

Online Query Tool for IKCEST EST Terms

From the high quality MOOC courses of Tsinghua University, the important knowledge points of these courses are extracted and presented by vivid multimedia, to improve the interest of the learners and guide learners’ deep learning.

Consisted of City Data and Best Practices, the World Observatory of Cities allows you to explore cities on 26 indicators and best practices on themes of Intelligent City, Eco-city and Industrial Heritage.

As urban planning discipline develops, the “knowledge” and “scholar” impact on the transformation, delivering and innovation raise the attention of the academia. Scholar Network focuses on the world urban planning knowledge network, regarding the regularity of knowledge and scholar elements as the aim of study. In phase 1 of Intelligent City Knowledge Service, our team finished the work of Scholar’s Network of Europe. We collected 81,988 pieces of research outputs data from 2,044 planning scholars out of 57 major European urban planning schools. Methods like data capturing, networking, visualization, semantic analysis and complex network analytical methods are adopted.

China is one of the countries with the most serious natural disasters in the world. Facing sudden major natural disasters, China has taken much effective disaster relief and got rich experiences in the past several serious disasters, and received widespread attention and praise from international society. Therefore, it is necessary to collect these typical disaster relief cases and share China’s nature disaster relief experiments to the world. This knowledge application tries to collect the knowledge information about the prevention before disaster, rescue in disaster and restoration after disaster. The Wenchuan earthquake, Zhouqu debris flow, and Jiuzhaigou earthquake are selected as typical cases. Serials of data, maps, pictures, videos, papers, planning reports and other related information about these cases are integrated in the content web interfaces.

To introduce the most representative major projects in contemporary China which involve energy, transportation and architecture, and so on, and the builders’ stories which display their extraordinary career skill and persistent and the excellence craftsman spirit.

Map Visualization Services of China Historical Disasters Desc: The DRR platform has published a lot of scanned maps online. Disaster maps of China are listed in the app page. User could get China historical disaster information from visualized maps which was developed based on WebGIS technology.

This Macroeconomic Database select many macroeconomic data indexes of all the counties along the Belt and Road in order to give reader a access to get related countries’ economic data. On the other hand, this database can also reflect those countries’ fast development in recent six years, due to the Belt and Road.

It has collected the online courses which are the favorite of national colleges along Silk Road including energy and power engineering, Chinese culture and history, IT, management and business, materials, and life science and technology, for users in demand.

The global daily earthquake data is fetched via the interface of USGS. Using Leafletjs to combine the data and MapBox tiles to generate the map view. When the app page opened, the daily realtime earthquake information can be visualized in the map services.

The majority organizations of disaster risk reduction have been collected and stored in the DRR platform. The data for the organization has been transferred into GeoJson format, had then been displayed on the map tiles of MapBox. User could find the organization by position on the map and get more navigation information (will be done later).

Considering the urgent demand for the spatio-temporal distribution of drought disasters over long periods of time in the Belt and Road region, this knowledge service utilized the Tropical Rainfall Measuring Mission satellite (TRMM) precipitation data to calculate the monthly spatio-temporal distribution of drought in the Belt and Road arable area from 2001 to 2013 based on the Precipitation Abnormity Percentage drought model. This application shows the monthly spatio-temporal distribution of the drought from 2001 to 2013. MapServer is used to release Web Map Service (WMS) referring the international specifications and standards. The combination of data and MapBox tiles are used by LeafletJS to generate the GIS map view. When the app page is opened, the GIS map could be visualized as the map service. Selecting GIS data operation in the sidebar navigation, users can see the corresponding options (year and month) and click the drop-down arrow to display the year and month lists, including the years from 2001 to 2013, and the months from January to December. Additional links (e.g. Data) are listed in the app page for users to get more related resources.

Poyang Lake is the largest freshwater lake in China, and it plays an important role in flood control regulation and storage and biodiversity protection.Water eutrophication in Poyang Lake has been considered to be an obstacle to aquatic environment protection and regional sustainable development. Chlorophyll-a concentration is one of the most important indices of water eutrophication. This application builds seasonal chlorophyll-a concentration retrieval models using a semi-analytical model. Quarterly distributions of chlorophyll-a concentration from 2009 to 2012 are explored using multi-spectra data from a moderate-resolution imaging spectroradiometer (MODIS). With the WebGIS technology, the application of spatial distribution of the seasonal chlorophyll-a concentration in Poyang Lake, China (2009-2012) has been released. This application shows the measured chlorophyll-a concentration data in January, April, July, and October from 2009 to 2012. MapServer is used to release Web Map Service (WMS) referring the international specification. The Combination of data and MapBox tiles has been used by OpenLayers to generate the map view. When the app page opened, the satellite image could be visualized as the map service. In the map operation on the right side of the app page, users can select different years and months to view the corresponding data map. Selecting GIS data operation in the sidebar navigation, users can see the corresponding options (year and month) and click the drop-down arrow to display the year and month lists, including the years from 2009 to 2012, and the months include January, April, July, and November. In the bottom right corner of the app page, users can see application-related documents and information which are classified by label control. The user can choose “more” to get more readings.

The University Alliance of the New Silk Road is a university alliance formed by Xi'an Jiaotong University and founded on May 22, 2015, with 128 universities from 31 countries. This module provides 128 web portals of the partner universities and displays the achievements in scientific research and relative papers.

The Silk Road knowledge graph covers diverse domains from sciences to government data. Users are able to use the knowledge graph to resolve their query and assemble the information by themselves without having to navigate to other sites in a straightforward prospective.

The featured database mainly refers to the six databases collected by the SRST Knowledge Service platform. Six featured databases collect mainly the “The Belt and Road Initiatives” countries’ multidisciplinary electronic resources, including journals, conferences, patents, monographs, standards and other document types for global users.

The Songliao Basin, China is crossed by the Songhua River and Liaohe River, spans 260,000 sq.km. across three provinces of Liaoning, Jilin, and Heilongjiang and four cities-Hulun Buer League, Xing'an League, Zenith (Tongliao City) and Chifeng City of Inner Mongolia. A cold and humid forest, meadows, and grassland comprise its landscape. The flood and waterlogging disasters in Songliao Basin has high frequency and wide range characteristics, and the loss of the disaster is aggravating year by year. Based on the reconnaissance and analysis technology, the spatial information and data of administrative division, landscape, soil, traffic road, river, lake, reservoir, basin range, flood, rainstorm and typhoon are preceded and sorted in this application. MapServer is used to release Web Map Service (WMS) referring the international specifications and standards. The combination of data and MapBox tiles are used by LeafletJS to generate the GIS map view. When the app page is opened, the GIS map could be visualized as the map service. The documents and information of basic geography, hydrology and flood disaster are classified and sorted by label control. Additional links for related resources are listed in the app page.

Concentrations of suspended solids in lakes can affect the latter’s primary productivity and reflect changes in sediment deposition. Determining the temporal and spatial distribution of suspended solid concentrations has important significance in lake water environmental management; this is particularly urgent for Poyang Lake, the largest freshwater lake in China. In this application, suspended solid concentration inversion models for Poyang Lake were created using a semi-empirical method with regression analysis between continuously measured suspended solid concentration data and multi-band moderate-resolution imaging spectroradiometer images for spring, summer, autumn, and winter from 2009 to 2012. The seasonal distributions of suspended solid concentrations in Poyang Lake from 2000 to 2013 were then obtained using optimal reversal models. With the WebGIS technology, the application of spatial distribution of the seasonal suspended solids concentration in Poyang Lake, China (2000-2013) has been released. This application shows the measured suspended solid concentrations data in January, February, April, July, October and December from 2000 to 2013. MapServer is used to release Web Map Service (WMS) referring the international specification. The Combination of data and MapBox tiles has been used by OpenLayers to generate the map view. When the app page opened, the satellite image could be visualized as the map service. In the map operation on the right side of the app page, users can select different years and months to view the corresponding data map. Selecting GIS data operation in the sidebar navigation, users can see the corresponding options (year and month) and click the drop-down arrow to display the year and month lists, including the years from 2000 to 2013, and the months include January, April, July, and October,. In the bottom right corner of the app page, users can see application-related documents and information which are classified by label control. The user can choose “more” to get more readings.

Data MORE
  • Monthly maximum temperature monitoring data set for south and southeast Asia (1989-2018)

    Monthly maximum temperature monitoring data set for south and southeast Asia (1989-2018)

    The data set is calculated and interpolated by weather station data. The meteorological site data comes from NOAA, which includes data such as temperature, wind speed, and precipitation. The research team processes the daily weather station data into monthly data, and then interpolates through Kriging to form raster data covering the entire study area.
  • Monthly minimum temperature monitoring data set for south and southeast Asia(1989-2018)

    Monthly minimum temperature monitoring data set for south and southeast Asia(1989-2018)

    The data set is calculated and interpolated by weather station data. The meteorological site data comes from NOAA, which includes data such as temperature, wind speed, and precipitation. The research team processes the daily weather station data into monthly data, and then interpolates through Kriging to form raster data covering the entire study area.
  • Monthly total precipitation monitoring data set for South Asia and southeast Asia(1989-2018)

    Monthly total precipitation monitoring data set for South Asia and southeast Asia(1989-2018)

    The data set is calculated and interpolated by weather station data. The meteorological site data comes from NOAA, which includes data such as temperature, wind speed, and precipitation. The research team processes the daily weather station data into monthly data, and then interpolates through Kriging to form raster data covering the entire study area.
  • Monthly mean station pressure monitoring data set for south and southeast Asia(1989-2018)

    Monthly mean station pressure monitoring data set for south and southeast Asia(1989-2018)

    The data set is calculated and interpolated by weather station data. The meteorological site data comes from NOAA, which includes data such as temperature, wind speed, and precipitation. The research team processes the daily weather station data into monthly data, and then interpolates through Kriging to form raster data covering the entire study area.
  • Monthly mean temperature monitoring data sets for south and southeast Asia(1989-2018)

    Monthly mean temperature monitoring data sets for south and southeast Asia(1989-2018)

    The data set is calculated and interpolated by weather station data. The meteorological site data comes from NOAA, which includes data such as temperature, wind speed, and precipitation. The research team processes the daily weather station data into monthly data, and then interpolates through Kriging to form raster data covering the entire study area.
  • Monthly average dew point monitoring data set in south and southeast Asia(1989-2018)

    Monthly average dew point monitoring data set in south and southeast Asia(1989-2018)

    The data set is calculated and interpolated by weather station data. The meteorological site data comes from NOAA, which includes data such as temperature, wind speed, and precipitation. The research team processes the daily weather station data into monthly data, and then interpolates through Kriging to form raster data covering the entire study area.
  • Historical mean wind speed monitoring data set for south and southeast Asia (1989-2018)

    Historical mean wind speed monitoring data set for south and southeast Asia (1989-2018)

    The data set is calculated and interpolated by weather station data. The meteorological site data comes from NOAA, which includes data such as temperature, wind speed, and precipitation. The research team processes the daily weather station data into monthly data, and then interpolates through Kriging to form raster data covering the entire study area.
  • Flood Disaster Loss Dataset in China (2018)

    Flood Disaster Loss Dataset in China (2018)

    This dataset is Flood Disaster Loss Dataset in China (2018). Using web crawlers, We gathered professional reports related to earthquakes from the website of China National Commission for Disaster Reduction (NCDR-China). A series of extraction rules were constructed to extract disaster loss data. The following information was extracted: disaster time, event title, location, number of deaths, number of missing persons, affected population, direct economic losses, and crop disaster area. The data format is Excel. The spatial scope is China. The temporal range 2018.
  • Spatio-temporal Distribution of Desertification Disaster along the China-Mongolia railway (Mongolia section) in 2000 and 2015

    Spatio-temporal Distribution of Desertification Disaster along the China-Mongolia railway (Mongolia section) in 2000 and 2015

    This dataset described the Spatio-temporal Distribution of Desertification Disaster along the China-Mongolia railway (Mongolia section) in 2000 and 2015, which mainly record the degree of desertification, and spatiotemporal distribution information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 6 vector files and 4 grid files. It can be used in the study of desertification. And it can provide important basis for monitoring and prevention of desertification disaster.
  • Weibo Sentiment Index DataSet related to the Flood in Shouguang, China (2018)

    Weibo Sentiment Index DataSet related to the Flood in Shouguang, China (2018)

    This dataset is Weibo Sentiment Index Data related to the Flood in Shouguang, China. Using web crawlers and Weibo API, original Weibo messages were collected with “Shouguang” as the keyword. The following information was extracted: user ID, timestamp (i.e., the time when the message was posted), text (i.e., the text message posted by a user), and location information. Then sentiment index was calculated by ‘Tencent’ natural language processing (NLP) API. The data format is Excel. The spatial scope is China. The temporal range is 00:00 on August 19 2018 and 00:00 on August 28 2018. There are 77,581 Weibo texts.
  • Meteorological resource database of

    Meteorological resource database of " Belt and Road" China-Mongolia-Russia economic corridor

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1990, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 21 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Earthquake disaster dataset (2010)

    Earthquake disaster dataset (2010)

    The data set is obtained from Baidu search and reference documents by means of data capture, collection and sorting, and describes some earthquake information about time, type of disaster, country, location, number of casualties, and so on. The dataset collects information on earthquake disasters in some countries in the Belt and Road in 2010. This data set can help users understand the time and spatial distribution of earthquakes and provide strong support for some scientific research related to earthquake disaster prevention.
  • Data set of heat wave frequency in South and Southeast Asia(1989-2018)

    Data set of heat wave frequency in South and Southeast Asia(1989-2018)

    The data set is calculated and interpolated from meteorological station data. Meteorological station data come from NOAA, including temperature, wind speed, precipitation and other data. The research team called the phenomenon that the maximum temperature of a station exceeded 35 degrees C for three consecutive days as a heat wave process, and then obtained the heat wave frequency of each station, and then formed the grid data covering the whole research area through Kriging interpolation.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 2018

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 2018

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2018, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 28 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 2017

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 2017

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2017, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 27 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 2016

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 2016

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2016, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 26 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1999

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1999

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1999, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 15 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1998

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1998

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1998, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 15 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1997

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1997

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1997, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 11 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1996

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1996

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1996, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 16 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1995

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1995

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1995, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 16 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1994

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1994

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1994, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 20 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1993

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1993

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1993, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 13 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1992

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1992

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1992, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 17vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1991

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1991

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1991, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 16 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1990

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area in 1990

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 1990, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 21 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Basic national information database of Ukraine

    Basic national information database of Ukraine

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Ukraine includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of The United Arab Emirates

    Basic national information database of The United Arab Emirates

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of The United Arab Emirates includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Slovakia

    Basic national information database of Slovakia

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Slovakia includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Moldova

    Basic national information database of Moldova

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Moldova includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Latvia

    Basic national information database of Latvia

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Latvia includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Israel

    Basic national information database of Israel

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Israel includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Georgia

    Basic national information database of Georgia

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Georgia includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Bulgaria

    Basic national information database of Bulgaria

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Bulgaria includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Belarus

    Basic national information database of Belarus

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Belarus includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Bahrain

    Basic national information database of Bahrain

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Bahrain includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Rainstorm and flood disaster in Shanghai 1949-2017

    Rainstorm and flood disaster in Shanghai 1949-2017

    The main contents of the rainstorm and flood disaster in Shanghai are the heavy rainstorm and flood disaster since the founding of the people's Republic of China (1949), including the time point or time period of the rainstorm and flood in the city of Shanghai, the degree of rainfall, the degree of rainstorm and flood (the depth of water accumulation in the city, the number of households in the household, the number of road accumulations), etc.
  • Lighting disaster in Shanghai 1961-2008

    Lighting disaster in Shanghai 1961-2008

    The main content of the lightning strike disaster set in Shanghai is the major lightning disaster from 1961 to 2008, mainly including the time point or time period and degree of lightning strikes in Shanghai.
  • High temperature disaster in Shanghai 1934-2018

    High temperature disaster in Shanghai 1934-2018

    The main content of the Shanghai high temperature disaster collection is the major high temperature disaster from 1934 to 2018, mainly including the time or period of high temperature occurrence in Shanghai, and the degree of high temperature.
  • Heave fog and haze disaster in Shanghai 1956-2008

    Heave fog and haze disaster in Shanghai 1956-2008

    The main content of the dense fog disaster in Shanghai is the major fog disaster from 1956 to 2008, which mainly includes the time or time period of dense fog in Shanghai, the degree of dense fog, etc.
  • Hail disaster in Shanghai 1917-1998

    Hail disaster in Shanghai 1917-1998

    The main content of the Shanghai Hail Disaster Collection is the major hail disaster from 1917 to 1998, mainly including the time point or time period of the occurrence of hail in Shanghai, and the degree of hail.
  • Gale disaster in Shanghai 1846-2006

    Gale disaster in Shanghai 1846-2006

    The main contents of the Shanghai gale disaster are the gale disasters from 1841 to 2006, mainly including the time points or time periods, the stations and the maximum wind speed, and so on in Shanghai city.
  • Drought disaster in Shanghai 1967-2006

    Drought disaster in Shanghai 1967-2006

    The main content of the Shanghai drought disaster collection is the major drought disaster from 1967 to 2006, mainly including the time or time period of drought in Shanghai, the degree of drought, etc.
  • Cold wave and heavy snow disaster in shanghai 1841-2008

    Cold wave and heavy snow disaster in shanghai 1841-2008

    The main content of the cold wave and heavy snow disasters in Shanghai is the major cold wave and heavy snow disaster from 1841 to 2008, mainly including the time point or time period and degree of occurrence of cold wave and heavy snow in Shanghai.
  • Rainstorm and flood disaster in Chongqing 1956-2018

    Rainstorm and flood disaster in Chongqing 1956-2018

    The main content of the rainstorm flood disaster in Chongqing is the major storms and floods from 1949 to 2018, mainly including the time or time period of rainstorms and floods in Tianjin, the extent of rainfall, heavy rains and floods (the depth of water in the city, the residents’ homes) The number of water users and the number of water accumulated in the road).
  • Low temperature and rainy in Chongqing 1953-2018

    Low temperature and rainy in Chongqing 1953-2018

    The main content of the low temperature and rainy disaster in Chongqing is the major storms and floods from 1949 to 2018, mainly including the time or time period of Low temperature and rainy in Chongqing, the extent ofLow temperature and rainy.
  • Lightning disaster in Chongqing 1955-2013

    Lightning disaster in Chongqing 1955-2013

    The main contents of the lightning disaster in Chongqing are the heavy lightning disaster since the founding of the people's Republic of China (1949), including the time point or time period of the lightning in the city of Chongqing, the degree of lightning disaster.
  • Landslide in Chongqing1986-2017

    Landslide in Chongqing1986-2017

    The main content of the landslide disaster in Chongqing is the major Landslide from 1949 to 2018, mainly including the time or time period of rainstorms and floods in Chongqing, the extent of Landslide.
  • Hail and wind in Chongqing 1966-2015

    Hail and wind in Chongqing 1966-2015

    The main contents of the Hail and wind disaster in Chongqing are the heavy Hail and wind disaster since the founding of the people's Republic of China (1949), including the time point or time period of the Hail and wind in the city of Chongqing, the degree of Hail and wind disaster.
  • Drought and high temperature in Chongqing1960-2018

    Drought and high temperature in Chongqing1960-2018

    The main content of the Drought and high temperaturer in Chongqing is the major storms and floods from 1949 to 2018, mainly including the time or time period ofDrought and high temperature in Chongqing, the extent of Drought and high temperaturer.
  • Debris flow disaster in Chongqing 1996-2001

    Debris flow disaster in Chongqing 1996-2001

    The main content of the debris flow disaster in Chongqing is the major Debris flow from 1949 to 2018, mainly including the time or time period ofDebris flow in Chongqing, the extent of Debris flow .
  • Dataset of desertification related land cover distribution along China-Mongolia railway (Mongolia section) in 2015

    Dataset of desertification related land cover distribution along China-Mongolia railway (Mongolia section) in 2015

    This dataset was the land cover distribution data related to desertification along the China-Mongolia railway (Mongolia section) in 2015. This dataset used the object-oriented remote sensing image interpretation method to obtain the desertification data with a resolution of 30 meters along the China-Mongolia railway (Mongolia section) in 2015. It was collected and organized by the Institute of Geographic Sciences and Natural Resources Research, CAS. It can be used to study the risk assessment of desertification in China-Mongolia railway, providing an important basis for preventing sandstorms, floods and other disasters caused by desertification and alleviating the negative impact of desertification.
  • Rainstorm and flood disaster data of 1950-2017  in Beijing

    Rainstorm and flood disaster data of 1950-2017 in Beijing

    The main contents of the rainstorm and flood disaster in Beijing are the heavy rainstorm and flood disaster since the founding of the people's Republic of China (1949), including the date of the rainstorm and flood in the city of Beijing, the degree of rainfall, the station,the daily rainfall,the max flood peak, etc.
  • Lightning disaster data of 1954-2014  in Beijing

    Lightning disaster data of 1954-2014 in Beijing

    The main contents of the lightning disaster in Beijing are the lightning disaster since 1954,including the date of the lightning disaster in the city of Beijing,the casualty,the economic losses, etc.
  • Hot-dry wind and high temperature data of 1960-2018  in Beijing

    Hot-dry wind and high temperature data of 1960-2018 in Beijing

    The main contents of the hot-dry wind and high temperature disaster in Beijing are the hot-dry wind and high temperature disaster since 1960, including the date of the hot-dry wind and high temperature disaster in the city of Beijing, etc.
  • Hail disaster data of 1950-2017 in Beijing

    Hail disaster data of 1950-2017 in Beijing

    The main contents of the hail disaster in Beijing are the hail disaster since 1950, including the date of the hail disaster in the city of Beijing, the snowfall,the hail diameter,the hail weight, the thickness of the hail on ground, the duration,etc.
  • Gale and Sand-dust Storm disaster data of 1954-2017 in Beijing

    Gale and Sand-dust Storm disaster data of 1954-2017 in Beijing

    The main contents of the gale disaster and sand-dust storm disaster in Beijing are the gale disaster and sand-dust storm disaster since1954, including the date of the gale disaster and sand-dust storm disaster in the city of Beijing, the wind scale,the wind speed,the type,etc.
  • Fog and haze disaster data of 1990-2017 in Beijing

    Fog and haze disaster data of 1990-2017 in Beijing

    The main contents of the fog and hazedisaster in Beijing are the fog and haze disaster since 1990, including the date of the fog and haze disaster in the city of Beijing, the visibility , etc.
  • Drought disaster  data of 1951-2014 in Beijing

    Drought disaster data of 1951-2014 in Beijing

    The main contents of the drought disaster in Beijing are the drought disaster since 1954, including the date of the drought disaster in the city of Beijing, the rainfall,the reservoir storage capacity,the water level drops,degree, etc.
  • Debris flow disaster data of 1949-2016 in Beijing

    Debris flow disaster data of 1949-2016 in Beijing

    The main contents of the Debris Flow Disaster in Beijing are the debris flow disaster since 1949, including the date of the debris flow disaster in the city of Beijing, the casualty,the house damage,etc.
  • Cold damage and snow damage data of 1952-2018 in Beijing

    Cold damage and snow damage data of 1952-2018 in Beijing

    The main contents of the cold damage and snow damage in Beijing are the cold damage and snow damage since 1952, including the date of the cold damage and snow damage in the city of Beijing, the snowfall,the snow depth,the glaze duration, temperature, instantaneous wind speed,etc.
  • Bangladesh, China, India and Myanmar's historical heat wave datasets of 1981 - 2018

    Bangladesh, China, India and Myanmar's historical heat wave datasets of 1981 - 2018

    This dataset is acquired from Google news, Wikipedia ,the Emergency Events Database and reference documentation by data crawl,collecting and arranging, which describes some heat wave information about time, disaster type,country,location,extreme temperature, et al. And the dataset counts the heat wave event occurred in Bangladesh, China, India and Myanmar from 1981AD to 2018AD, which includes 76 data in total. This dataset can help user to know the temporal and spatial distribution of heat wave occurrence, and provide strong support for some heat wave prevention and mitigation and related scientific research.
  • Bangladesh, China, India and Myanmar's historical flood datasets of 1981 - 2018

    Bangladesh, China, India and Myanmar's historical flood datasets of 1981 - 2018

    This dataset is acquired from Google news, Wikipedia ,the Emergency Events Database and reference documentation by data crawl,collecting and arranging, which describes some flood information about year, disaster type,country,total deaths,injured, et al. And the dataset counts the flood event occurred in Bangladesh, China, India and Myanmar from 1981AD to 2018AD, which includes 130 data in total. This dataset can help user to know the temporal and spatial distribution of flood occurrence, and provide strong support for some flood prevention and mitigation and related scientific research.
  • Bangladesh, China, India and Myanmar's historical earthquake datasets of 1981- 2018

    Bangladesh, China, India and Myanmar's historical earthquake datasets of 1981- 2018

    This dataset is acquired from Google news, Wikipedia ,the Emergency Events Database and reference documentation by data crawl,collecting and arranging, which describes some earthquake information about year, disaster type,country,total deaths,injured, et al. And the dataset counts the earthquake event occurred in Bangladesh, China, India and Myanmar from 1981AD to 2018AD, which includes 69 data in total. This dataset can help user to know the temporal and spatial distribution of earthquake occurrence, and provide strong support for some earthquake prevention and mitigation and related scientific research.
  • Bangladesh, China, India and Myanmar's historical drought datasets of 1981- 2018

    Bangladesh, China, India and Myanmar's historical drought datasets of 1981- 2018

    This dataset is acquired from Google news, Wikipedia ,the Emergency Events Database and reference documentation by data crawl,collecting and arranging, which describes some drought information about year, disaster type,country,total deaths,injured, et al. And the dataset counts the drought event occurred in Bangladesh, China, India and Myanmar from 1981AD to 2018AD, which includes 38 data in total. This dataset can help user to know the temporal and spatial distribution of drought occurrence, and provide strong support for some drought prevention and mitigation and related scientific research.
  • Bangladesh, China, India and Myanmar's historical cold wave datasets of 1981 - 2018

    Bangladesh, China, India and Myanmar's historical cold wave datasets of 1981 - 2018

    This dataset is acquired from Google news, Wikipedia ,the Emergency Events Database and reference documentation by data crawl,collecting and arranging, which describes some cold wave information about time, disaster type,country,location,extreme temperature, et al. And the dataset counts the cold wave event occurred in Bangladesh, China, India and Myanmar from 1981AD to 2018AD, which includes 67 data in total. This dataset can help user to know the temporal and spatial distribution of cold wave occurrence, and provide strong support for some cold wave prevention and mitigation and related scientific research.
  • Web news text dataset of drought in China(2006-2018)

    Web news text dataset of drought in China(2006-2018)

    This web news text dataset of drought in China is gathered by a web crawler from the SINA.com, which is an online news media source with the largest user group in China. The dataset includes title, time, and text. The data format is Excel. The spatial scope is China. The temporal range is 2004-2018.There are 1646 drought news text.
  • Web news text dataset of flood in China(2006-2018)

    Web news text dataset of flood in China(2006-2018)

    This web news text dataset of flood in China is gathered by a web crawler from the SINA.com, which is an online news media source with the largest user group in China. The dataset includes title, time, and text. The data format is Excel. The spatial scope is China. The temporal range is 2004-2018.There are 1889 flood news text.
  • Web news text dataset of typhoon in China(2004-2018)

    Web news text dataset of typhoon in China(2004-2018)

    This web news text dataset of typhoon in China is gathered by a web crawler from the SINA.com, which is an online news media source with the largest user group in China. The dataset includes title, time, and text. The data format is Excel. The spatial scope is China. The temporal range is 2004-2018.There are 3445 typhoon news text.
  • Web news text dataset of earthquake in China(2005-2018)

    Web news text dataset of earthquake in China(2005-2018)

    This web news text dataset of earthquake in China is gathered by a web crawler from the SINA.com, which is an online news media source with the largest user group in China. The dataset includes title, time, and text. The data format is Excel. The spatial scope is China. The temporal range is 2005-2018.There are 5339 earthquake news text.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2015

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2015

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2015, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 24 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2014

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2014

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2014, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 20 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2013

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2013

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2013, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 35 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2012

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2012

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2012, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 18 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2011

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2011

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2011, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 16 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2010

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2010

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2010, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 20 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2009

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2009

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2009, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 26 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2008

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2008

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2008, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 26 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2007

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2007

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2007, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 25 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2006

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2006

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2006, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 37 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area of 2005

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area of 2005

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2005, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 33 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area of 2004

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area of 2004

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2004, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 25 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area of 2003

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area of 2003

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2003, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 23 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area (2002)

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area (2002)

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2002, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 19 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area (2001)

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area (2001)

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2001, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 19 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2000

    Spatio-temporal Distribution of Earthquake Disaster in the Belt and Road Area during 2000

    This dataset described the distribution of earthquake disasters in countries along the Belt and Road in 2000, which mainly record the seismic location, earthquake grade, seismic wave coverage and range information. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. This dataset was composed of 19 vector files. They could be used to study the occurrence and distribution of earthquake disasters, and provided an important basis for preventing earthquake disasters and reducing the negative impact of earthquake disasters.
  • Data Resources in Europe and America

    Data Resources in Europe and America

    Information Technology Development, Disaster Prevention and Reduction, Medical Health, Manufacturing Industry, Urban Development, Environmental and Resource in Europe and America
  • EDS external library

    EDS external library

    Academic Journals, Magazines, Trade Publications, News, Books, Reviews, Reports, Conference Materials, Dissertations, Theses, Biographies, Primary Source Documents, Government Documents, Music Score, Research Starters, Electronic Resources, Non-Print Resources
  • Engineering Transactions of CAE

    Engineering Transactions of CAE

    Engineering is aimed at the provision of a high-level platform where academic achievements of great importance in engineering science and technology can be disseminated and shared.
  • Food and Food Safety

    Food and Food Safety

    It includes some frontier information, industry report, science and technology report, scientific data about food and food safety from AMIS, USDA, etc.
  • Storm Prediction Report

    Storm Prediction Report

    The National Weather Service Storm Prediction Center (SPC) provides daily RSS feeds summarizing today's latest information about tornado and severe thunderstorm watches, mesoscale discussions, convective day 1-3 outlooks, and fire weather outlooks. Although available to all, the data provided may be of particular value to weather professionals and students of meteorological sciences.
  • Science Festival Company Sponsors

    Science Festival Company Sponsors

    The Austin Energy Regional Science Festival is one of the largest regional science festivals held in Texas and the nation. Middle and high school students who win at their respective schools compete at the regional festival to advance to the state science fair competition. Five senior level projects receive Best of Fair awards and the winners of those projects have the option to advance directly to the international competition. Central Texas middle and high school students have performed very well at past state and international competitions. Between 2004 and 2016, 100 students representing 71 projects advanced to the international level. Of those, 44 students representing 29 projects won 73 category and special awards. Since 2004, more than 1,225 students have advanced to the state level, where about 20% have won awards. In 2016, the Austin Energy Regional Science Festival showcased 755 middle and high school projects. Unlike most regional events, Austin Energy also hosts elementary school students. Nearly 4,000 students and their families turn out for the event which includes a public viewing of the science projects as well as educational booths and scientific demonstrations. Over 550 judges and 180 volunteers from the City of Austin, local businesses, colleges, and elementary/middle/high schools contribute annually to the event’s success. Revenues to fund the event come from fees paid by participating schools and companies that provide sponsorships.
  • Traditional Neighborhood Development (TND)

    Traditional Neighborhood Development (TND)

    boundaries of zoning overlay districts as adopted by the UDO in 2013
  • Building a Better Austin: Action Steps

    Building a Better Austin: Action Steps

    Action steps for Development Services Department (DSD) and Planning and Zoning Department (PAZ) to address the Zucker final report received in May 2015. Additional information is located at www.austintexas.gov/roadmap.
  • New Base Zoning (effective Dec. 24, 2014)

    New Base Zoning (effective Dec. 24, 2014)

    The new Zoning Ordinance is effective December 24, 2014. This map represents the new overlay zoning districts within the City of Providence. For more information related to the districts and uses, you can find the new ordinance online at: http://providenceri.iqm2.com/Citizens/Detail_LegiFile.aspx?Frame=&MeetingID=2469&MediaPosition=&ID=4631&CssClass
  • Affordable Rental Housing Developments

    Affordable Rental Housing Developments

    The affordable rental housing developments listed below are supported by the City of Chicago to maintain affordability standards. For information on rents, income requirements and availability, contact each property directly. For information on other affordable rental properties in Chicago and Illinois, call (877) 428-8844, or visit www.ILHousingSearch.org.
  • New Home Builders

    New Home Builders

    The Office of Consumer Protection (OCP) licenses builders or anyone acting in the capacity of a building contractor who constructs new homes in Montgomery County. This data consists of all active new home builder license holders. OCP does not license home improvement (ex. repair, remodeling, partial replacement, addition, or modernization, of existing structure) contractors; these contractors are licensed by Maryland Home Improvement Commission. The license information is deemed to be reliable, but we cannot guarantee the accuracy and completeness of the information. Any information that is shown to be inaccurate will be corrected if brought to the attention of OCP. Data Update Frequency : Daily
  • Maryland Total New Parcels Inside PFA For Residential Development: 2006-2015

    Maryland Total New Parcels Inside PFA For Residential Development: 2006-2015

    Maryland Total New Parcels inside Priority Funding Areas (PFA) for residential development from 2006 through and including 2015 based on the PFA boundaries and MdProperty View Edition year data referenced below. PFAs are existing communities and places where local governments want State investment to support future growth. 2006-2012 Data Sources: -PFA boundaries dated 08/21/2014 -MdProperty View 2012 Edition for all jurisdictions except Allegany and Garrett counties, which are based on MdProperty View 2011 Edition updated with August 2014 parcel data from the State Department of Assessments and Taxation. 2013-2015 Data Sources: -PFA boundaries dated 08/29/2016 -MdProperty View 2013/14 Edition parcel data for all jurisdictions in Maryland except the following: Baltimore, Caroline, Cecil, Dorchester, Harford, Kent, Queen Anne’s, Talbot, and Wicomico counties and Baltimore City, 2013/2014 Edition data updated with June 2016 parcel data from Assessments, and Anne Arundel and Carroll Counties, 2012 Edition data updated with June 2016 parcel data from Assessments. For new parcels included in the June 2016 update, parcel point placement was done via geocoding and not via placement by deed and/or plat.
  • Indoor Plumbing Program FY13

    Indoor Plumbing Program FY13

    The Indoor Plumbing Program is a sub-set of the Maryland Rehabilitation Loan Program. Numbers are tracked individually, when the rehabilitation work involves strictly plumbing, sewer and water related improvements. Often times IPP improvements/rehabilitation is done as part of a larger project and the funding does not reflect in these numbers.
  • Pittsburgh City Facilities

    Pittsburgh City Facilities

    Pittsburgh City FacilitiesIncludes: City Administrative Buildings, Police Stations, Fire Stations, EMS Stations, DPW Sites, Senior Centers, Recreation Centers, Pool Locations, Ballfields,  Libraries,  Park Play Areas, Tennis Courts, and Utility BuildingsMetadata: https://www.arcgis.com/sharing/rest/content/items/b9c387d024944503ad27549e196d7260/info/metadata/metadata.xml?format=default[HTML_REMOVED]output=html
  • Seattle Parks and Recreation Lifelong Recreation (50+) Trip Participation

    Seattle Parks and Recreation Lifelong Recreation (50+) Trip Participation

    This dataset contains geographic statistics for trip participation in the Lifelong Recreation (50+) program. Lifelong Recreation (50+) programs focus on physical activity, social engagement, education, arts, creativity, and healthy lifestyles for older adults.
  • Public Electric Vehicle Charging Stations and Alternative Fuel Stations in Maryland

    Public Electric Vehicle Charging Stations and Alternative Fuel Stations in Maryland

    It takes a lot of fuel to move Marylanders from point “A” to point “B.” The Maryland Energy Administration (MEA) offers incentives to reduce the amount of energy residents expend on travel. This table includes information about electric vehicle charging stations and alternative refueling stations that received funding by MEA as well as those that did not. Data on non-MEA funding projects in Maryland is from the U.S. Department of Energy: http://1.usa.gov/13VN2Vi. For more information on Maryland's transportation programs, visit: http://energy.maryland.gov/Transportation/index.html
  • Hospitals and Urgent Care Facilities

    Hospitals and Urgent Care Facilities

    Locations of the hospitals and urgent care centers within Fairfax County.
  • Capital Improvement Projects - Points

    Capital Improvement Projects - Points

    Selected FCDOT capital improvement projects (points) included in the Transportation Status Report.
  • Building Footprints (current)

    Building Footprints (current)

    Building footprints in Chicago. Metadata may be viewed and downloaded at http://bit.ly/HZVDIY. The data can be viewed on the Chicago Data Portal with a web browser. However, to view or use the files outside of a web browser, you will need to use compression software and special GIS software, such as ESRI ArcGIS (shapefile) or Google Earth (KML or KMZ), is required.
  • PMIS 2013

    PMIS 2013

    The Pavement Management Information Systems (PMIS) from 2011 through 2015 contains various levels of data on the pavement condition and history of Iowa Interstate and Primary routes. The data was collected by a 3rd party vendor and processed by the Iowa Department of Transportation. Starting in 2013, the data is reported in English Units instead of Metric Units.
  • MTA Transit Oriented Development (TOD) Data

    MTA Transit Oriented Development (TOD) Data

    DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station. The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station. As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations. You can view an interactive version of this dataset at geodata.md.gov/tod. * Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.
  • Recorded Flood Plains

    Recorded Flood Plains

    The approximate location of the 100 year floodplain easement as shown on record plats within Fairfax County. This does not show all floodplains in the County, only ones where studies have been performed and submitted on a recorded plat.
  • Capital Improvement Projects - Lines

    Capital Improvement Projects - Lines

    Selected FCDOT capital improvement projects (lines) included in the Transportation Status Report.
  • Water Supply Watershed Overlay Districts

    Water Supply Watershed Overlay Districts

    boundaries of zoning overlay districts as adopted by the UDO in 2013
  • DBEDT Currently Proposed Renewable Energy Projects In Hawaii

    DBEDT Currently Proposed Renewable Energy Projects In Hawaii

    DBEDT Currently Proposed Renewable Energy Projects In Hawaii
  • Loudoun Rt 28 Optional Overlay District

    Loudoun Rt 28 Optional Overlay District

    More MetadataThis layer identifies the Route 28 Optional Overlay Districts in Eastern Loudoun County. The districts provide additional development options for the properties mapped as specified in Article 4 Division D of the Revised 1993 Zoning Ordinance.Purpose:This layer is used to depict the properties along the Route 28 Corridor that are mapped for the Rt. 28 Optional Overlay Districts. The Rt. 28 Optional Overlay Districts are intended to provide planned development and incentive zoning as tools to coordinate new development with the Route 28 Corridor Plans goals and objectives.
  • New York Power Authority Net Generation (MWh) Produced by Facility: Beginning 2013

    New York Power Authority Net Generation (MWh) Produced by Facility: Beginning 2013

    The New York Power Authority is America's largest state power organization, with 16 generating facilities and more than 1,400 circuit-miles of transmission lines.The data provided includes megawatt-hours produced net of station service by each NYPA facility.
  • Chicago Energy Benchmarking - Covered Buildings

    Chicago Energy Benchmarking - Covered Buildings

    The full list of buildings required to comply with the Chicago Energy Benchmarking Ordinance. As of 2016, this list includes all commercial, institutional, and residential buildings larger than 50,000 square feet. The information in this dataset should be used by building owners / managers or other building representatives to determine if your property needs to comply by the annual deadline of June 1st. This data can also be used to look up your property's unique 6-digit Chicago Energy Benchmarking ID, which is required for compliance. (The ID is also included the notification letters sent by the City.) The Energy Benchmarking Ordinance calls on existing municipal, commercial, and residential buildings larger than 50,000 square feet to track whole-building energy use, report to the City annually, and verify data accuracy every three years. The law, which phases in from 2014-2017, covers less than 1% of Chicago’s buildings, which account for approximately 20% of total energy used by all buildings. For more details, including ordinance text, rules and regulations, and timing, please visit www.CityofChicago.org/EnergyBenchmarking. Note that the ordinance authorizes the City to make individual building data readily-available to the public, beginning with the second year in which a building is covered. The Covered Buildings List is distinct from the publicly-shared energy use data, and does not include energy use or any other information reported in the benchmarking process. For the building-specific energy use dataset, see https://data.cityofchicago.org/d/xq83-jr8c. If your property is on this list, and you do not believe you are covered by the ordinance, please submit the appropriate online exemption form at: www.CityofChicago.org/EnergyBenchmarking. If your property is not on the list, and it meets the compliance criteria, please check for any alternative building addresses. If the building is still not found, please submit the Building ID Request Form (http://www.cityofchicago.org/city/en/depts/mayor/iframe/Benchmarking_ID_Request.html). The Chicago Energy Benchmarking Help Center can assist with any other questions, and can be reached at (855)858-6878, or by email: Info@ChicagoEnergyBenchmarking.org. This dataset will be refreshed periodically as additional information becomes available. It is advisable to use the then-current version of any dataset, if possible.
  • Lottery Aid to Education

    Lottery Aid to Education

    Aid to education provided by the New York Lottery by fiscal year, by county, by school district
  • Youth and Family Initiative All Top Priorities

    Youth and Family Initiative All Top Priorities

    Results from 131 Community Caucuses, five large group workshops, the Youth Summit and via the web for Mayor Mike McGinn’s Youth and Families Initiative.
  • Tuition Assistance Program (TAP) Recipients & Dollars by College, Sector Group, and Level of Study: Beginning 2000

    Tuition Assistance Program (TAP) Recipients & Dollars by College, Sector Group, and Level of Study: Beginning 2000

    The Tuition Assistance Program (TAP), New York's largest student financial aid grant program, helps eligible New York residents attending in-state postsecondary institutions pay for tuition. TAP grants are based on the applicant’s and his or her family’s New York State taxable income. This data includes TAP award recipients and dollar amounts by college, sector groups, and Level of Study for academic years 2000-2011.
  • Pittsburgh FEMA Flood Zones

    Pittsburgh FEMA Flood Zones

    Pittsburgh FEMA Flood Zones 2014Metadata: https://www.arcgis.com/sharing/rest/content/items/fb45ed8f9e0d463aadfab95620ffa303/info/metadata/metadata.xml?format=default[HTML_REMOVED]output=html
  • Earthquake Locations

    Earthquake Locations

    This layer has been compiled from various sources depicting the locations of earthquakes that have been confirmed to have occurred within the state of North Dakota. Constraints: Not to be used for navigation, for informational purposes only. See full disclaimer for more information.
  • Investing in Innovation 2011 Applications

    Investing in Innovation 2011 Applications

    Thank you for your interest in the Investing in Innovation (i3) Program! You can use the tools below to look at general information about the applications, and you can also find specific applications that you would like to explore in more detail. The data is sourced from supplemental forms as reported by applicants. The data from these forms may not be a full or accurate representation of the information provided in the formal application.
  • Pittsburgh Landslide Prone

    Pittsburgh Landslide Prone

    Pittsburgh Landslide Prone AreasMetadata: https://www.arcgis.com/sharing/rest/content/items/c5b8bed5963746d4844dcfea7c2053e7/info/metadata/metadata.xml?format=default[HTML_REMOVED]output=html
  • Building Data

    Building Data

    Explore real estate information about buildings in the Town of Cary.This file is created by the Town of Cary GIS Group. It contains data from both the Wake, Chatham Counties real estate data. It has been modified from the original sources to act as one layer for use by the Town of Cary. This file is updated once a month from the respective sources. Please refer to each Counties data from the latest information.
  • Chicago Public Schools - Safe Passage Routes SY1617

    Chicago Public Schools - Safe Passage Routes SY1617

    Chicago Public Schools, in partnership with parents, the Chicago Police Department (CPD) and City of Chicago, has expanded the District's successful Safe Passage Program to provide safe routes to and from school every day for your child. This map presents the Safe Passage Routes specifically designed for designated schools during the 2016-2017 school year. To view or use these shapefiles, compression software, such as 7-Zip, and special GIS software, such as Google Earth or ArcGIS, are required.
  • Street Sweeping - 2017 - Map

    Street Sweeping - 2017 - Map

    Street sweeping zones by Ward and Ward Section Number. For the corresponding schedule, see https://data.cityofchicago.org/d/iry7-etg6. For more information about the City's Street Sweeping program, go to http://bit.ly/H2PHUP. The data can be viewed on the Chicago Data Portal with a web browser. However, to view or use the files outside of a web browser, you will need to use compression software and special GIS software, such as ESRI ArcGIS (shapefile) or Google Earth (KML or KMZ).
  • Areas Damaged by Fire Following 1906 Earthquake

    Areas Damaged by Fire Following 1906 Earthquake

    GIS (shapefile) boundary of areas damaged by fire following the 1906 earthquake. This layer was digitized from a raster image of the historic paper map entitled "San Francisco, California, showing the areas destroyed by fire, April 18-21, 1906". The paper map was published by R.J. Waters & Co. in 1906. Scale [ca. 1:21,000]. Raster map downloaded from the Harvard Map Collection, Harvard College Library, Cambridge, Massachusetts: http://ids.lib.harvard.edu/ids/view/7271039?buttons=y
  • Bike Rack Locations Downtown Pittsburgh

    Bike Rack Locations Downtown Pittsburgh

    List of bike rack locations, capacity and type for Downtown Pittsburgh.
  • Transportation Projects in Your Neighborhood

    Transportation Projects in Your Neighborhood

    This data set contains DOT construction project information. The data is refreshed nightly from multiple data sources, therefore the data becomes stale rather quickly.
  • SNOwpack TELemetry Network (SNOTEL)

    SNOwpack TELemetry Network (SNOTEL)

    The SNOTEL data retrieval tools provides an interactive process to identify and retrieve data from individual SNOTEL sites. The user does not need to know the ID for the site but must know either it's general location or the name of the site
  • Pothole Tracking

    Pothole Tracking

    Potholes reported and filled by the the Department of Public works.
  • Charm City Circulator Ridership

    Charm City Circulator Ridership

    The City of Baltimore is constantly seeking innovative and creative ways to alleviate traffic congestion and green house gases in our great city. A new fleet of eco-friendly buses will provide everyone with a faster, more convenient, greener way to move about Baltimore's busy downtown neighborhoods. This data reflects the daily passengers boarding and alighting for each route. In order to get to one ��_��_��_neat��_�� ridership number, an average of the boarding and alighting numbers is calculated to get a final count. The disparity in the boarding and alighting counts can be contributed to the difficulty the sensors encounter with small children, large groups, wheelchairs, strollers, etc.
  • SSMMA TIP Projects

    SSMMA TIP Projects

    This dataset outlines projects funded under the Transportation Improvement Program within the SSMMA Jurisdiction
  • Urban Trails

    Urban Trails

    The Urban Trails dataset describes a specific type of pedestrian and bicycle-user infrastructure. The ideal design of an Urban Trail is an off-street, 12 foot wide concrete path that can accommodate a variety of trail users including bicyclists, pedestrians, wheel chair users, parents with strollers, kids on razor scooters and so on. Since the first Urban Trails Master Plan was adopted in September 2014 not all existing trail segments in this dataset strictly comply with the guidelines described in Appendix A: Trail Design Criteria of the Urban Trails Master Plan. The Urban Trails network is intended to be a part of the greater Active Transportation Network and may relate to the on-street bicycle network or the sidewalk network, as well as City of Austin parks. In this dataset, many Urban Trail endpoints connect to the City of Austin’s streets dataset or the City of Austin’s parks dataset. The data in this feature class was created by the amalgamation of three datasets: the Parks and Recreation Trail Layer (based on their Long Range Facilities Master Plan), the Neighborhood Planning Implementation Layer, and feedback and comments received during the Urban Trail Master Plan process (October 2012-September 2014) For more information, the Urban Trails Master Plan can be found here: http://www.mediafire.com/view/qusnf4qg3h4v4z7/UTMP_online.pdf
  • Recurring Resident Economic Empowerment and Sustainability Programs

    Recurring Resident Economic Empowerment and Sustainability Programs

    Regulary occuring REES programs
  • Oklahoma Institutions of Higher Education

    Oklahoma Institutions of Higher Education

    Find higher education facilities in the state of Oklahoma.
  • DYCD after-school programs: ISY In-School Youth Employment Programs

    DYCD after-school programs: ISY In-School Youth Employment Programs

    Facilities in New York City, by agency and site, that offer “In-School Youth Employment (ISY) Program” after-school job and internship programs for students in High School.
  • ATR Continuous Count Sites

    ATR Continuous Count Sites

    This REST service depicts the continuous count Automatic Traffic Recorder (ATR) location sites in the state of Iowa.
  • United States Renewable Energy Technical Potential

    United States Renewable Energy Technical Potential

    Renewable energy technical potential as defined in this report represents the achievable energy generation of a particular technology given system performance, topographic limitations, environmental, and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential—resource, technical, economic, and market—each seen in Figure 1 (below), with key assumptions.
  • RAMS - Traffic ATR Location

    RAMS - Traffic ATR Location

    Traffic ATR Location data maintained inside the Roadway Asset Management System (RAMS).
  • Alternative Service Locations - RV Dump Station

    Alternative Service Locations - RV Dump Station

    Iowa Department of Transportation statewide rest area data. This layer displays alternative service locations that have an RV dump station.
  • PMIS 2012

    PMIS 2012

    The Pavement Management Information Systems (PMIS) from 2011 through 2015 contains various levels of data on the pavement condition and history of Iowa Interstate and Primary routes. The data was collected by a 3rd party vendor and processed by the Iowa Department of Transportation. Starting in 2013, the data is reported in English Units instead of Metric Units.
  • Housing New York Units by Project

    Housing New York Units by Project

    The Department of Housing Preservation and Development (HPD) reports on buildings, units, and projects that began after January 1, 2014 and are counted towards the Housing New York plan. The Housing New York Units by Project file presents this data by project, and includes project-level data, such as senior units, but does not include building-level data. The unit counts are provided for each project, rather than by building. For additional documentation, including a data dictionary, review the attachments in the “About this Dataset” section of the Primer landing page.
  • Department of Information Technology- Performance Dashboard- Major IT Development Projects (Annual)

    Department of Information Technology- Performance Dashboard- Major IT Development Projects (Annual)

    This dataset identfies the number of major IT development projects for the Department of Information Technology on an annual basis.
  • DYCD after-school programs: NDA Educational Middle School Programs

    DYCD after-school programs: NDA Educational Middle School Programs

    Facilities in New York City, by agency and site, that offer “Neighborhood Development Area (NDA) Educational Middle School Programs” after-school programs for children in Middle School.
  • Maryland Total Acres Inside PFA For Residential Development: 2006-2015

    Maryland Total Acres Inside PFA For Residential Development: 2006-2015

    Maryland Total Acres inside Priority Funding Areas (PFA) for residential development from 2006 through and including 2015 based on the PFA boundaries and MdProperty View Edition year data referenced below. PFAs are existing communities and places where local governments want State investment to support future growth. 2006-2012 Data Sources: • PFA boundaries dated 08/21/2014 • MdProperty View 2012 Edition for all jurisdictions except Allegany and Garrett counties, which are based on MdProperty View 2011 Edition updated with August 2014 parcel data from the State Department of Assessments and Taxation. 2013-2015 Data Sources: • PFA boundaries dated 08/29/2016 • MdProperty View 2013/14 Edition parcel data for all jurisdictions in Maryland except the following: Baltimore, Caroline, Cecil, Dorchester, Harford, Kent, Queen Anne’s, Talbot, and Wicomico counties and Baltimore City, 2013/2014 Edition data updated with June 2016 parcel data from Assessments, and Anne Arundel and Carroll Counties, 2012 Edition data updated with June 2016 parcel data from Assessments. For new parcels included in the June 2016 update, parcel point placement was done via geocoding and not via placement by deed and/or plat.
  • Erosion Hazard Zone Review Buffer

    Erosion Hazard Zone Review Buffer

    This dataset was created to show all areas where an erosion hazard zone analysis will be required for any proposed development. THIS LAYER DOES NOT REPRESENT A CALCULATED EROSION HAZARD ZONE. It simply indicates whether or not an erosion hazard zone analysis is needed per LDC (see below). Effective October 28, 2013, the City’s Land Development Code §25-7-32 allows: “ The director may require … an analysis to establish the erosion hazard zone if the proposed development is within 100 feet of the centerline of a waterway with a drainage area of 64 acres or greater; or where significant erosion is present. ”
  • Fuquay-Varina Utility As-Built Drawings

    Fuquay-Varina Utility As-Built Drawings

    These polygons represent development projects for subdivisions, commercial projects, town utility expansions, and other development relevant to public infrastructure. Attributes for these polygons include a hyperlink to browse all available public [HTML_REMOVED]As-Built[HTML_REMOVED] record drawing files. These are all free to download for non-commercial use, since the contents are sometimes copyrighted material belonging to developers or engineering firms. ToFV GIS is striving to have its entire as-built archive represented spatially, but it will take some time for older developments to be processed. Please contact us if you have any specific questions or concerns.
  • Primary Commercial Zoning by lot

    Primary Commercial Zoning by lot

    Primary Zoning by lot Based on PLUTO 2005
  • Capital Project Schedules and Budgets

    Capital Project Schedules and Budgets

    List of capital projects with managing organization, phase status and project costs.
  • DYCD after-school programs: NDA Educational High School Progams

    DYCD after-school programs: NDA Educational High School Progams

    Facilities in New York City, by agency and site, that offer “Neighborhood Development Area (NDA) Educational High School Programs” after-school programs for children in High School.
  • Active Projects Under Construction

    Active Projects Under Construction

    New school projects (Capacity) and Capital Improvement Projects (CIP) currently under Construction.
  • Iowa School Districts 2016-2017

    Iowa School Districts 2016-2017

    Iowa School Districts as maintained by the Iowa Department of Education, effective 7/1/2016. Efforts are ongoing to improve the accuracy of Iowa school district boundaries. Boundaries are verified with local officials and edited to conform with the legal description wherever possible. Boundaries are updated annually to account for reorganizations.
  • DYCD after-school programs: Runaway And Homeless Youth

    DYCD after-school programs: Runaway And Homeless Youth

    Facilities in New York City, by agency and site, that offer after-school programs for runaway and homeless youth, including street outreach programs, drop-in centers, crisis shelters, and transitional independent living (TIL) programs.
  • IPTV Educational Services Outreach Events

    IPTV Educational Services Outreach Events

    This data catalogs Iowa Public Television's Education Services Division staff engagement with Iowa teachers, students, caregivers and parents using PBS Learning Media, Classroom Connections, Ready for School or Ready to Learn materials and programming starting in July 2010 through the current month.
  • Capacity Projects  by schools

    Capacity Projects by schools

    Capacity project detail by school.
  • DYCD after-school programs: OSY Out Of School Youth Employment Programs

    DYCD after-school programs: OSY Out Of School Youth Employment Programs

    Facilities in New York City, by agency and site, that offer “Out-Of -School Youth Employment (OSY) Program” after-school job and internship programs for young adults ages 16 to 21.
  • 2009 - 2010 Graduation Outcomes - Regents-based Math- ELA APM - School Level

    2009 - 2010 Graduation Outcomes - Regents-based Math- ELA APM - School Level

    Graduation Outcomes - Class of 2010 - Math/ELA Aspirational Performance Measure (APM) ¶•The New York State Education Department adopted Aspirational Performance Measures (APM) in addition to high school graduation rates for the Cohort of 2006 (Class of 2010). In addition to the numbers of students earning Advanced Regents Designation on their diplomas, another metric was developed based on performance on Math and ELA Regents exams. The Math/ELA APM represents the percentage of students in the cohort who graduated with any regular diploma (Regents Diploma with Advanced Designation, Regents Diploma, or Local Diploma) and who scored 80 or greater on their highest mathematics Regents and 75 or greater on the English Regents. Since this metric is new for the Class of 2010, only one year of results is reported, separately for June and August graduation cohorts. The total number of students in the cohort is the same in June and August. ¶•Records with cohorts of 20 students or less are suppressed. ¶•August outcomes include all June and August graduates. ¶•In school-level reporting, students who were in a school for less than 5 months are not included in the school’s cohort, but are included in citywide totals. ¶•School level results are not presented for District 79 schools, but their outcomes are included in citywide totals. ¶•Schools that had previously obtained a waiver to use alternative assessments (rather than Regents examinations) were omitted from the Math/ELA APM calculations.
  • Congress District Breakdowns

    Congress District Breakdowns

    Demographic statistics broken down by congress districts
  • Energy Usage From DOE Buildings

    Energy Usage From DOE Buildings

    Energy data from a select portfolio of City-owned buildings (DOE)
  • Seattle Police Department 911 Incident Response

    Seattle Police Department 911 Incident Response

    This dataset is all the Police responses to 9-1-1 calls within the city. Police response data shows all officers dispatched. To protect the security of a scene, the safety of officers and the public, and sensitive ongoing investigation, these events are added to the data.seattle.gov only after the incident is considered safe to close out. Data is refreshed on a 4 hour interval.
  • DYCD after-school programs: Beacon Satellite At NYCHA Programs

    DYCD after-school programs: Beacon Satellite At NYCHA Programs

    Facilities in New York City, by agency and site, that offer “Beacon Satellite at NYCHA Programs” after-school programs.
  • Assembly District Breakdowns

    Assembly District Breakdowns

    Demographic statistics broken down by assembly districts
  • ISP - Firearm Owners' Identification (FOID) Applications

    ISP - Firearm Owners' Identification (FOID) Applications

    FOID Card Applications -- 10 Year History -- 2002 through 2011
  • Envista Projects for Utility Excavation and Paving

    Envista Projects for Utility Excavation and Paving

    Envista Projects for Utility Excavation and Paving. Envista is used by city agencies and private utilities to coordinate utility and paving work in public right of way.
  • Storm Detention Areas

    Storm Detention Areas

    Town of Cary Stormwater Network
  • Storm Line

    Storm Line

    The Town of Fuquay-Varina creates, maintains, and serves out a variety of utility information to the public, including its Stormwater Drainage System features. This collection of stormwater system data includes some layers designated as private that are not owned or maintained by the Town, but are important for modeling and other informational purposes. These layers are created and maintained by ToFV GIS, and are updated frequently.
  • Flood Prone Soils

    Flood Prone Soils

    Flood Prone Soils Additional FEMA information available: https://msc.fema.gov/portal
  • Envista Projects for Paving

    Envista Projects for Paving

    Envista Projects for Paving. Envista is used by city agencies and private utilities to coordinate utility and paving work in public right of way.
  • ISP - Firearm Transfer Inquiry (FTIP) Requests

    ISP - Firearm Transfer Inquiry (FTIP) Requests

    FTIP Inquiry Requests -- 10 Year History -- 2002 through 2011
  • CBU Service Building Energy and Water Consumption

    CBU Service Building Energy and Water Consumption

    Electricity, natural gas, and water consumption data for the City of Bloomington Service Building.
  • Storm Clean Outs

    Storm Clean Outs

    Town of Cary Stormwater Network
  • Beach Weather Stations - Automated Sensors

    Beach Weather Stations - Automated Sensors

    The Chicago Park District maintains weather sensors at beaches along Chicago's Lake Michigan lakefront. These sensors generally capture the indicated measurements hourly while the sensors are in operation during the summer. During other seasons and at some other times, information from the sensors may not be available. See https://data.cityofchicago.org/id/qmqz-2xku for a dataset with similar measurements on the lake water, itself. The sensor locations are listed at https://data.cityofchicago.org/d/g3ip-u8rb.
  • Seattle Parks and Recreation GIS Map Layer Shapefile - Envirnomental Learning Centers

    Seattle Parks and Recreation GIS Map Layer Shapefile - Envirnomental Learning Centers

    Seattle Parks and Recreation GIS Map Layer Shapefile - Envirnomental Learning Centers Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/13
  • Storm Open Drains

    Storm Open Drains

    Town of Cary Stormwater Network
  • IEMA Federal Disaster Declarations by County

    IEMA Federal Disaster Declarations by County

    A list of Federally Declared Disaster by Illinois County since 1965.
  • Storm Fittings

    Storm Fittings

    Town of Cary Stormwater Network
  • Storm Gravity Mains

    Storm Gravity Mains

    Town of Cary Stormwater Network
  • Green Building Aggregate Data

    Green Building Aggregate Data

    Austin Energy Green Building ratings evaluate the sustainability of participating single family, multifamily and commercial buildings on a scale of one to five stars in the areas of energy efficiency, water efficiency, materials, site, indoor environmental quality, community impact and innovation. View the program performance savings metrics achieved since Fiscal Year 2007. Learn more at http://greenbuilding.austinenergy.com.
  • Storm Virtual Drainlines

    Storm Virtual Drainlines

    Town of Cary Stormwater Network
  • Storm Network Structures

    Storm Network Structures

    Town of Cary Stormwater Network
  • FEMA Disaster Reimbursements

    FEMA Disaster Reimbursements

    This dataset contains a list of disasters from 2000 to the present in which Montgomery County received FEMA reimbursements. Update Frequency : As Needed
  • County Emergency Management Offices

    County Emergency Management Offices

    This dataset lists the County, Emergency Manager Name, Address and Office Phone Number for all Emergency Management Offices within NYS. The New York State Office of Emergency Management (OEM) and its predecessor agencies have been responsible for coordinating the activities of all State agencies to protect New York's communities, the State's economic well-being, and the environment from natural and man-made disasters and emergencies.
  • Stuttgart local weather data archive

    Stuttgart local weather data archive

    Weather data from two weather stations at Stuttgart Rice Research and Extension center are archived. Current air temperature, relative humidity, wind speed, solar radiation and soil temperature data are provided by station and are displayed and archived either hourly or daily. Historical weather data goes back to 2008.
  • USDA Service Center Locator

    USDA Service Center Locator

    This site provides addresses, telephone numbers and other key information for USDA Service Center locations. These office locations will provide customers with information and assistance for available disaster programs. Agencies shown include the Farm Service Agency, Rural Development and the Natural Resources Conservation Service.
  • Performance Metrics - City Colleges of Chicago - Course Success Rates

    Performance Metrics - City Colleges of Chicago - Course Success Rates

    Course Success rate is the percent of students obtaining grades A‐C and P out of the total number of students enrolled at the beginning of the term. Course success is the building block toward student program completion. Without successful completion of courses, City Colleges of Chicago students will not be able to earn credits toward a degree or certificate, nor will they progress from remedial to college-level coursework.
  • College Access Challenge Grant Program (CACGP) Subgrantees: 2008-2016

    College Access Challenge Grant Program (CACGP) Subgrantees: 2008-2016

    The overall goal of New York's College Access Challenge Grant (CACG) is to increase the number of low-income, minority and underserved students who are prepared to apply for, get accepted to and succeed in college, with a priority on families living below the poverty-level.This data includes the names of the organizations that received CACGP sub-grants during the Award Period, the number of students and families that received (or will receive) services from the sub-grantee, and the grant amount awarded to each organization.
  • Energy and Water Use - Municipal Buildings

    Energy and Water Use - Municipal Buildings

    In the spirit of leading by example, the City released benchmarking information for municipal buildings. The data includes property name, location, property size (ft²), Energy STAR scores where available, energy intensity (kBTU/ft²), water use (kilo-gallons), total GHG emissions (Metric Tons CO₂e), and several more metrics.
  • School District Breakdowns

    School District Breakdowns

    Demographic statistics broken down by school districts
  • 2015 Building Energy Benchmarking

    2015 Building Energy Benchmarking

    Seattle’s Building Energy Benchmarking and Reporting Program (SMC 22.920) requires owners of non-residential and multifamily buildings (20,000 square feet or larger) to track energy performance and annually report to the City of Seattle. Buildings account for 33% of Seattle's core emissions. The benchmarking policy supports Seattle's goals to reduce energy use and greenhouse gas emissions from existing buildings. In 2013, the City of Seattle adopted a Climate Action Plan to achieve zero net greenhouse gas (GHG) emissions by 2050. Annual benchmarking, reporting and disclosing of building performance are foundational elements of creating more market value for energy efficiency. Per Ordinance (125000), starting with 2015 energy use performance reporting, the City of Seattle will make the data for all building 20,000 SF and larger available annually. This update to the benchmarking mandate was passed by Seattle City Council on February 29, 2016. If you have questions or comments on the data, email us at energybenchmarking@seattle.gov and include Open Data in the subject line.
  • Moving!! - SDOT Pothole Work Order [arcgis_rest_services_SDOT_EXT_DSG_datasharing_MapServer_1]

    Moving!! - SDOT Pothole Work Order [arcgis_rest_services_SDOT_EXT_DSG_datasharing_MapServer_1]

    This dataset will be moving! The City is working on a new Open Data Portal for GIS data. This dataset will soon be available at https://data-seattlecitygis.opendata.arcgis.com/. We apologize for any inconvenience, but this new platform will allow us to regularly update our data and provided better tools for our spatial data. http://gisrevprxy.seattle.gov/arcgis/rest/services/SDOT_EXT/DSG_datasharing/MapServer/1
  • Seattle Parks and Recreation GIS Map Layer Shapefile - Fire Pits

    Seattle Parks and Recreation GIS Map Layer Shapefile - Fire Pits

    Seattle Parks and Recreation GIS Map Layer Shapefile - Fire Pits Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/14
  • Beach Water Quality - Automated Sensors

    Beach Water Quality - Automated Sensors

    The Chicago Park District maintains sensors in the water at beaches along Chicago's Lake Michigan lakefront. These sensors generally capture the indicated measurements hourly while the sensors are in operation during the summer. During other seasons and at some other times, information from the sensors may not be available. See https://data.cityofchicago.org/d/k7hf-8y75 for a dataset with land-based weather measurements at selected beaches. The sensor locations are listed at https://data.cityofchicago.org/d/g3ip-u8rb.
  • Sustainable Green Infrastructure Monitoring Sensors

    Sustainable Green Infrastructure Monitoring Sensors

    Results from City-installed sensors measuring water runoff from streets and sidewalks. These data can be used to measure the impact of sustainable green infrastructure on flooding. These sensors also capture weather data. Each row corresponds to a sensor measurement at a specific time and location. Each row is a different sensor, which can be determined from the "Measurement Title" column. The value for each measurement is always numeric and available in the "Measurement Value" column. The corresponding unit of measurement is in the "Units" column. Data may be missing at times due to sensors not being available.
  • Hartford GIS Data

    Hartford GIS Data

    This data set will give the user access to our enterprise GIS Data layers through our ArcGIS Online Open Data website. Data is always current to our GIS data.
  • Comprehensive Plan - Base Recommendation

    Comprehensive Plan - Base Recommendation

    Planned land use at the baseline level. Refer to the Comprehensive Plan text for interpretation and for options above the baseline level. This layer has been updated to include Amendment 2013-28, adopted by the BOS October 20, 2015 and all previous amendments.
  • Waterfront Access Plans

    Waterfront Access Plans

    GIS data: A waterfront access plan (WAP) is a specific plan, set forth in the Zoning Resolution that tailors waterfront bulk regulations and public access requirements to the specific conditions of a particular waterfront area.
  • Water cover data of Mongolia with spatial resolution of 30m(1990)

    Water cover data of Mongolia with spatial resolution of 30m(1990)

    This dateset was water cover data of Mongolia, one of the subsets of Mongolian land cover dataset. It used the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Ice cover data of Mongolia with spatial resolution of 30m(1990)

    Ice cover data of Mongolia with spatial resolution of 30m(1990)

    This dateset was ice cover data of Mongolia, one of the subsets of Mongolian land cover dataset. It used the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Grassland cover data of Mongolia with spatial resolution of 30m(1990)

    Grassland cover data of Mongolia with spatial resolution of 30m(1990)

    This dateset was grassland cover data of Mongolia, one of the subsets of Mongolian land cover dataset. It used the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Forest cover data of Mongolia with spatial resolution of 30m(1990)

    Forest cover data of Mongolia with spatial resolution of 30m(1990)

    This dateset was forest cover data of Mongolia, one of the subsets of Mongolian land cover dataset. It used the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Cropland cover data of Mongolia with spatial resolution of 30m(1990)

    Cropland cover data of Mongolia with spatial resolution of 30m(1990)

    This dateset was cropland cover data of Mongolia, one of the subsets of Mongolian land cover dataset. It used the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Built area cover data of Mongolia with spatial resolution of 30m(1990)

    Built area cover data of Mongolia with spatial resolution of 30m(1990)

    This dateset was built area cover data of Mongolia, one of the subsets of Mongolian land cover dataset. It used the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Barren cover data of Mongolia with spatial resolution of 30m(1990)

    Barren cover data of Mongolia with spatial resolution of 30m(1990)

    This dateset was barren cover data of Mongolia, one of the subsets of Mongolian land cover dataset. It used the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Estimation of Grassland Production in the Three-River Source Region Based on Remote Sensing, 2006-2015

    Estimation of Grassland Production in the Three-River Source Region Based on Remote Sensing, 2006-2015

    An accurate estimation of grassland production can provide scientific basis for informed decision-making on regional resource exploitation and socio-economic sustainable development. The dateset of grassland production in the Three-River Source Region contains information on the temporal and spatial changes of grassland production in the region from 2006 to 2015. The data sources of this dataset are measurement data, remote sensing data and auxiliary data. This dataset use MOD13Q1, MOD17A2, and MOD17A2H remote sensing data as data sources, the data resolution is 500m. With the ArcGIS software platform, data preprocessing such as projection conversion, boundary cutting was performed. The grassland production in the Three-River Source Region was estimated by statistical modeling and optimal model selection.
  • Basic national information database of Romania

    Basic national information database of Romania

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Romania includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Yemen

    Basic national information database of Yemen

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Yemen includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Poland

    Basic national information database of Poland

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Poland includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Palestine

    Basic national information database of Palestine

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Palestine includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Lebanon

    Basic national information database of Lebanon

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Lebanon includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Hungary

    Basic national information database of Hungary

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Hungary includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Estonia

    Basic national information database of Estonia

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Egypt includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Egypt

    Basic national information database of Egypt

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Egypt includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Czech Republic

    Basic national information database of Czech Republic

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Czech Republic includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of  Jordan

    Basic national information database of Jordan

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Jordan includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Southwest China's historical seismic datasets of 26AD - 2015AD

    Southwest China's historical seismic datasets of 26AD - 2015AD

    This dataset was acquired from China Earthquake Networks Center by data crawl, which described some earthquake information about time, latitude, longitude, depth, magnitude, et al. And the dataset counted the earthquake event occurred in Qinghai, Sichuan, Tibet and Yunnan from 26AD to 2015 AD, which included 8684 data in total. This dataset could help user to know the temporal and spatial distribution of earthquake occurrence, and provided strong support for some earthquake prevention and mitigation and related scientific research.
  • The dataset of restoration degree of forest vegetation in southern China

    The dataset of restoration degree of forest vegetation in southern China

    The assessment on the restoration degree of damaged and unrestored forest vegetation contributes to the management of forest resources and improve the restoration model of forest vegetation, which is of great significance for restoration of forest vegetation after disaster. The EVI data of 2008-2015 is selected as the main data sources. We used the coefficient of variation method to assess the restoration degree of damaged forest vegetation. The higher the coefficient of variation, the higher the degree of restoration of forest vegetation. This dataset can be used for research on post-disaster forest vegetation restoration.
  • The dataset of risk assessment of ice-snow disaster in southern China

    The dataset of risk assessment of ice-snow disaster in southern China

    Risk assessment of ice-snow disaster contributed to understand the probability and spatial distribution of that, which was of great significance for disaster prevention and reduction work. In this dataset, five indicator factors including daily average temperature, daily average precipitation, elevation, slope direction, and slope were selected to participate in the assessment work. The expert knowledge score method was used to determine the weights of the four indicators of precipitation, elevation, slope, and aspect. The average temperature was regarded as the most critical factor, which decided whether the area suffered from ice-snow disaster. The risk assessment value of ice-snow disaster was calculated, which was normalized. The dataset could be used for post-disaster related research.
  • Publications

    Publications

    To provide important works of engineering education at home and abroad, mainly including title, author, press, ISSN, and abstract in Chinese and English. It is helpful for experts, researchers, technicians and students in engineering colleges to understand and learn brief information of theories, research results and practical experience in engineering education.
  • The flood disaster database of Songliao basin in northeast of China

    The flood disaster database of Songliao basin in northeast of China

    Based on the reconnaissance and analysis technology, the format tables for flood disaster data of Songliao basin are preceded and sorted through data collection and analysis. The initial information had been preceded and finished with excluding irrelevant contents and leaving the relevant parameter information to meet the requirements of database. Finally, performing quality control measures have been taken, including self- checking and checking again by others. The assemble database which is after sorting is made into a file library. The disaster cases, causes and affection of flood, rainstorm,typhoon were extracted from the file library to build the flood disaster database of Songliao basin.
  • The hydrologic database of Songliao basin in northeast of China

    The hydrologic database of Songliao basin in northeast of China

    Based on the reconnaissance and analysis technology,the data set is made up of the reconnaissance and analysis results and the interpretation of remote sensing, and the spatial reference (projection and coordinate system) is Albers. The survey results images are derived and read in software ArcMap, using a variety of tools for a map, based on the scale of standard framing way of interpretation, the formation of vector data is formed into the file. Finally, the data is exported in the vector file. The hydrologic data of river, lake, reservoir and the basin range were extracted from the file library to build the hydrologic database of Songliao basin.
  • The basic geographic database of Songliao basin in northeast of China

    The basic geographic database of Songliao basin in northeast of China

    Based on the reconnaissance and analysis technology, the data set is made up of the reconnaissance and analysis results and the interpretation of remote sensing, and the spatial reference (projection and coordinate system) is Albers. The survey results images are derived and read in software ArcMap, using a variety of tools for a map, based on the scale of standard framing way of interpretation, the formation of vector data is formed into the file. Finally, the data is exported in the vector file.The data of administrative division, landscape, soil, vegetation , land use, traffic road and residential elevation were extracted from the file library to build the basic geographic database of Songliao basin.
  • Statistics of annual earthquake disaster losses in China (1990-2015)

    Statistics of annual earthquake disaster losses in China (1990-2015)

    The dataset of annual earthquake disaster losses in China plays an important role in the earthquake disaster prevention and its relief. By querying books, articles and website resources, this dataset collects the specific time, latitude and longitude, administrative region, magnitude, focal depth, the level and number of casualties, the damage level and area of houses, direct economic losses, the highest intensity, the population and area of Affected region, the damages of water conservancy facilities, the damages of education and health facilities, and the mental influence to people of 793 main annual earthquake disasters from 1990 to 2015.
  • Spatio-temporal distribution of drought in the Belt and Road Area during 1998-2015 based on TRMM precipitation data

    Spatio-temporal distribution of drought in the Belt and Road Area during 1998-2015 based on TRMM precipitation data

    The spatio-temporal distribution of drought information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. Based on the Tropical Rainfall Measurement Satellite (TRMM) 3B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of OBOR area from 1998 to 2015.
  • The drought level database of cropland in Belt and Road Area from 2001 to 2013

    The drought level database of cropland in Belt and Road Area from 2001 to 2013

    Based on the Tropical Rainfall Measurement Satellite (TRMM) 3B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of OBOR area from 2001 to 2013. Yearly spatio-temporal distribution from 2001 to 2013 of cropland in OBOR area was extracted based on the MODIS MCD12Q1 dataset and there were 156 monthly drought levels in the cropland region according to the overlaying of drought and agricultural land layers.
  • Land use/cover data of Mongolia with spatial resolution of 30m(2010)

    Land use/cover data of Mongolia with spatial resolution of 30m(2010)

    This dateset provides land use/cover data of Mongolia, with the spatial resolution of 30m, using the Albers projection, based on WGS-1984 geographic coordinate system. This data was interpreted on the basis of Landsat TM/etm+ remote sensing image and has 9 first classes including forest land, grassland, wet land, cultivated land, water, tundra,construction land, bare land and snow.The classfication accuracy is 82.26% and can be used for the study of land use/cover change in Mongolia, land management, planning and design of urban city.
  • Snow and ice disaster intensity across southern China in 2008

    Snow and ice disaster intensity across southern China in 2008

    The meteorological data, as the most important and significant factor in ice-snow disaster, plays an important role in the assessment of disaster intensity and disaster prediction. Based on professional software--Anusplin, the meteorological data that include day average temprature and day average precipitation are interpolated, combined with DEM data. The dataset covers ten provinces in southern China, which includes Hunan, Jiangxi, Guizhou, Chongqing, Guangxi, Guangdong, Fujian, Hubei, Anhui and Zhejiang Province. And the temporal range of this dataset is from 2008/01/10 to 2008/02/02. This dataset can be used to extract the spatial distribution of ice-frozen according to the standard from Chinese National Climate Center.
  • The diagnostic dataset of damaged vegetation restoration based on phenology information

    The diagnostic dataset of damaged vegetation restoration based on phenology information

    The diagnostic data of damaged vegetation restoration can reflect plant restoration status in time, and provide effective support for disaster recovery and reconstructions of affected vegetation. This dataset is produced by the spatial distribution of damaged vegetation and corresponding plant phenology data, which use the dynamic threshold method to monitor whether the damaged vegetation is restored or not. The dataset covers the whole of Hunan province, China, which includes 101 counties and the spatial resolution of which is 250 meters. What's more, the diagnostic result of vegetation restoration is from 2008 to 2015, the pixel value of which represents the recovery time. This dataset can be used in forest resource management and related scientific research.
  • Vegetation phenology data based on EVI time series

    Vegetation phenology data based on EVI time series

    The vegetation phenology data can reflect the plant growth status on a certain extent, which is an important tool for describing global climate change and terrestrial ecosystem responses. This dataset is produced by a professional software--TIMESAT, which runs on the Matlab environment and can extract the vegetation phenology data with vegetation indices time series. Using the method of the time series reconstructions algorithm (S-G filtering) , the enhanced vegetation index is selected as source data to various phenology data in this dataset, which covers 4 region (h27v05, h27v06, h28v05 and h28v06). The phenology can be used as vegetation growth foctor to monitor the vegetation growth condition.
  • The assessment of damaged vegetation caused by ice-snow disaster

    The assessment of damaged vegetation caused by ice-snow disaster

    The damaged degree of forest ice-snow frozen disaster contributes to reduce the loss of forest resources and forest ecosystem management, which is of great significance to the restoration of forest vegetation. This datasets are divided into two parts: the spatial distribution of damaged vegetation and evaluation on forest losses. Based on the dynamic threshold method, NDVI data is selected to extract the damaged forest caused by ice-snow disaster in 2008 and assess the forest losses. This dataset can be used to post-disaster various researches.
  • Historical earthquake data for China

    Historical earthquake data for China

    This dataset is acquired from China Earthquake Networks Center by data crawl, which describes some earthquake information about time, latitude, longitude, depth, magnitude, et al. And the dataset counts the earthquake event occurred in China from 780 BC to 2015 AD, which includes 15398 data in total. This dataset can give user the information about temporal and spatial distribution of earthquake occurrence, and provide strong support for earthquake prevention, mitigation and related scientific research.
  • Earthquake data of 1990-2015 in Qinghai - Tibet Plateau

    Earthquake data of 1990-2015 in Qinghai - Tibet Plateau

    This dataset is acquired from China Earthquake Networks Center by data crawl, which specifically describes some earthquake information about time, latitude, longitude, depth, magnitude, the disaster scope, the degree of damage, death toll et al. And the dataset counts the earthquake event occurred in Qinghai-Tibet Plateau from 1990 to 2015, which includes 161 data in total. This dataset can give users the information of temporal and spatial distribution of earthquake occurrence, provide a base data for earthquake prevention research in the area, and enrich the disaster prevention and mitigation knowledge service system data content.
  • Basic national information database of Indonesia

    Basic national information database of Indonesia

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Indonesia includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Iran

    Basic national information database of Iran

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Iran includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Iraq

    Basic national information database of Iraq

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Iraq includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Yemen

    Basic national information database of Yemen

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Yemen includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Armenia

    Basic national information database of Armenia

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Armenia includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Syria

    Basic national information database of Syria

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Syria includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Singapore

    Basic national information database of Singapore

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Singapore includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Brunei

    Basic national information database of Brunei

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Brunei includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Turkey

    Basic national information database of Turkey

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Turkey includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Sri Lanka

    Basic national information database of Sri Lanka

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Sri Lanka includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Malaysia

    Basic national information database of Malaysia

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Malaysia includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Kuwait

    Basic national information database of Kuwait

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Kuwait includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Qatar

    Basic national information database of Qatar

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Qatar includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Timor-Leste

    Basic national information database of Timor-Leste

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Timor-Leste includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Azerbaijan

    Basic national information database of Azerbaijan

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Azerbaijan includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Oman

    Basic national information database of Oman

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Oman includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Basic national information database of Afghanistan

    Basic national information database of Afghanistan

    The basic geographical national information data of countries and regions along the Belt and Road, is an important basis for disaster risk reduction. The basic geographical national information dateset of Afghanistan includes three categories, namely, basic national condition, natural resources, politics and economy. The detaial elements in the classification include geographical location, administrative division, topography, soil, climate, rivers and lakes, environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports, hospital bed density, etc.
  • Publications

    Publications

    The latest scientific and technical documents of the world's leading engineering and technical publishers
  • Open Source Software

    Open Source Software

    Converges the data real time from two open source websites of GitHub and SourceForge, and makes the classification navigation, providing convenient search of software tools for researchers and practitioners in engineering and technology fields.
  • Top College Textbooks

    Top College Textbooks

    Europe and the United States professional courses, teaching materials (including name, author, publishing house) and other data
  • Leaf Area Index (LAI): Field Measurements, Remote Sensing Estimation and Validation Studies

    Leaf Area Index (LAI): Field Measurements, Remote Sensing Estimation and Validation Studies

    Leaf area index (LAI) corresponds to one half the total green leaf area per unit horizontal ground surface area. It is one of the essential climate variables identified by the Global Climate Observing System (GCOS) and has been applied in a range of biosphere-atmosphere, biogeochemical, and ecological models as a primary biophysical and ecological parameter. This talk consists of three parts. The first part presents the LAI ground measurement methods. In the field, LAI can be estimated directly or indirectly: the direct methods measure LAI through litterfall or destructive sampling; the indirect methods estimate LAI via relationship with other more easily measurable parameters, such as canopy transmittance. The second part is about the LAI estimation from optical remote sensing technique. Current methods for estimating LAI are classified into three categories through: (1) the empirical relationship between LAI and vegetation indices; (2) inversion of canopy reflectance models; and (3) a hybrid inversion method. Following this, several major global LAI products and their spatial and temporal properties will be introduced. The last part of the presentation focuses on how to validate remote sensing LAI products. There are several validation schemes that develop uncertainty information about the global LAI products, such as the direct comparison method, the bridging method that makes comparison with upscaled high resolution products, and the cross-validation method.
  • ISCU World Data System :Trusted Data Serices for Globel Open Siences

    ISCU World Data System :Trusted Data Serices for Globel Open Siences

    Research is increasingly international, transdisciplinary, and data-enabled, which requires scrupulous data stewardship, full and open access to data. New expectations on researchers from governments and funders to share data fully, openly, and in a timely manner present significant challenges and opportunities to improve quality, efficiency and accountability to society. Researchers should be able to archive and disseminate data, and civil society to scrutinize datasets. Trustworthiness of data services must be verifiable. In addition, the need to integrate large and complex datasets across disciplines and domains with variable levels of maturity calls for better coordination to achieve interoperability and sustainability. WDS promotes long-term stewardship of, and universal and equitable access to, quality-assured scientific data. It coordinates and supports trusted scientific data services for the provision, use, and preservation of datasets to facilitate scientific research. It certifies its members—holders and providers of data—using internationally recognized standards, providing the building blocks of a searchable common infrastructure from which a data system that is both interoperable and distributed can be formed. This presentation will describe more specifically activities developed by its Scientific Committee to:(1)Improve and stimulate basic level Certification for Scientific Data Services, in particular through collaboration with the Data Seal of Approval. (2)Identify and define best practices for Publishing Data and to test implementation by involving the core stakeholders i.e. researchers, institutions, data centres, scholarly publishers, and funders.(3)Establish an open WDS Metadata Catalogue, Knowledge Network, and Global Registry of Trusted Data Services.
  • Treads and variability in atmospheric Precipitable water over the Tibetan Plateau

    Treads and variability in atmospheric Precipitable water over the Tibetan Plateau

    Trends and variability in precipitable water (PW) are an important component of climate change assessments for the Tibetan Plateau (TP). PW products from Moderate Resolution Imaging Spectroradiometer (MODIS) are able to provide good spatial coverage of PW over the TP. The trends and variations in TP PW from 2000 to 2010 are analysed using three different methods (including linear fit, non-parametric and non-linear). The trend patterns derived from MODIS and ECMWF are very similar except for the magnitude. Increasing trends are found in the eastern and western TP; with decreasing trends in the middle. To detect the decadal trend in PW over the TP, Bayesian inference theory is used to construct long-term and spatially continuous PW data for the TP based on the station and MODIS observations. The prior information on the monthly-mean PW from MODIS and the 63 stations over the TP for 2000–06 is used to get the posterior probability knowledge that is utilized to build a Bayesian estimation model. This model is then operated to estimate continuous monthly-mean PW for 1970–2011 and its performance is evaluated using the monthly MODIS PW anomalies (2007–11) and annual GPS PW anomalies (1995–2011) to demonstrate that the model estimation can reproduce the PW variability over the TP in both space and time. Annual PW series show a significant increasing trend of 0.19mmdecade21 for the TP during the 42 years. The most significant PW increase of 0.47mmdecade21 occurs for 1986–99 and an insignificant decrease occurs for 2000–11. From the comparison of the PW data from JRA-55, ERA-40, ERA-Interim, MERRA, NCEP-2, and ISCCP, it is found that none of them are able to show the actual long-term trends and variability in PW for the TP as the Bayesian estimation.
  • Socio-economic survey based impact assessment of herders’livelihood in the grasslands of Mongolia Plateau

    Socio-economic survey based impact assessment of herders’livelihood in the grasslands of Mongolia Plateau

    This presentation consists of two part: first part will brief the collaboration activities in the Mongolia Plateau, including the establishment of International Joint Research Center on Environment and Sustainable Development of Mongolian Plateau and it major collaboration progress. Second part will introduce the research progress on Socio-economic survey based impact assessment of herders’ livelihood in the grasslands of Mongolia Plateau. The second part will (1) brief the background for the survey, which is mainly due to severe eco-environment problems in the regions, eg, soil erosion, land degradation, limited water availability, extraction of mineral resources, overgrazing, and ecosystem deterioration, trade-offs between grassland ecosystem protection and economic development in the marginal lands, and increasing meat and dairy consumption and demand for land productivity. Actions taken to mitigate those problems are mainly ecosystem conservation programs, which affect herders’ living, this study aims to identify and assess these impact using socio-economic methods and approaches. (2) Designing and implementing the surveys (questionnaire survey, institutional survey): which include purposive/homogeneous sampling, determination of survey sites, sampling methods and conducting survey. (3) livelihood indicators derived from surveys and assessment: land resources, grazing patterns, income structure, consumption patterns, cost for production and grazing, and dependence on local ecosystem services. (4) Evaluation of the survey approaches applied.
  • Data sharing on Cryosphere in China

    Data sharing on Cryosphere in China

    His main research interests are remote sensing in Cryosphere and Data Sharing. He has developed two important databases: Chinese glacier inventory and glacial lake inventory in the Hindu-Kush Himalaya Region. The former has been included by GLIMS database and is also part of Randolph Glacier Inventory(RGI), which is cited by IPCC AR5. He is the key member of “Cold and Arid Regions Science Data Center at Lanzhou” which is the sub center of the earth system science data sharing platform and the regular member of World Data System. Cryosphere data(include snow, glacier and permafrost dataset), desert and desertification data, environmental and ecosystem data in inland basin can be free accessed from this data center.
  • Pattern and dynamic analysis of Northeast Asia land cover based on object-oriented classification method

    Pattern and dynamic analysis of Northeast Asia land cover based on object-oriented classification method

    Collecting Landsat TM/ETM+ images of the whole region in 1990~2000, with the support of the object-oriented platform Ecognition, this research used decision tree and nearest neighbors classifier to extract the information about the land cover pattern of Northeast Asia, as well as its dynamic change. Based on the above datasets, choosing the involved area of China-Russia treaty, the coastwise transect area of Heilongjiang river basin, transect area of the frozen soils and Wusuli river basin of cross-boundary region between China and Russia as priority areas in this study, we discussed characteristics of land cover patterns and spatial differences of changes among different countries. Besides, taking related research about land suitable assessment as reference, we selected the most sensitive, most accurate and most abundant information indices as the assessment factor, according to the principle of comprehensiveness, leading character, rank character and regional rules. Then, we combined AHP (analytic hierarchy process) and expert evaluation method to illustrate the weight of different evaluation factors. After that, we did comprehensive suitable evaluation of reserved cultivated land in Northeast Asia. Finally, this study determined the spatial patterns and quantity of general suitable zone, highly suitable zone, fairly unsuitable zone and unsuitable zone. The result of this study can provide scientific support for sound land use policy makings.
  • Ecosystem, climate and livelihood

    Ecosystem, climate and livelihood

    Ecosystem, climate and livelihood are closely related,this presentation will introduce five main topics :(1)Ecosystem, its Services and Management.(2)Evolution and Ecological Civilization.(3)Ecosystems and Sustainable Development. (4)Climate Change and ecosystems. (5)Ecosystem, Climate and Livelihood, towards a conceptual framework. Finally we will introduce Agenda 2030/SDGs,aimed at an array of issues that included slashing poverty, hunger, disease, gender inequality, and access to water and sanitation.It has 17 SD Goals/169 Targets,and is a conceptual framework of the Ecosystem, Climate and Livelihood, which to end poverty, fight inequality and injustice, and tackle climate change.
  • Global land cover mapping and change monitoring with Landsat data

    Global land cover mapping and change monitoring with Landsat data

    Introduce the first 30m resolution global land cover map – Finer Resolution Observation and Monitoring – Global Land Cover (FROM-GLC), its mapping philosophy and procedure based on Landsat and other Earth observation satellite data. Then introduce the follow up data products in the FROM family – FROM-Global Cropland, FROM – Water, FROM – Wetland, Afirca Land Cover, Chilean Land Cover,Major Cities, Regional Settlement. Some of the scientific applications based on these data products will also be presented. Lastly, we propose an international cooperation framework in support of national land cover mapping and change monitoring based on the procedural framework of FROM – GLC in collaboration with national experts from specific countries.
  • Qinghai Lake case:Databases,data analysis and applications

    Qinghai Lake case:Databases,data analysis and applications

    We will introduces the cyberinfrastructure, database and its applications in Qinghai Lake region. We have been building a cyberinfrastructure to support the protection and research in this area since 2006. We introduce the e-Science application practices supporting research on species identification, spatial distribution patterns analysis, and avian influenza virus cross-species infection by presenting their methods, implementation, and results. This is the first attempt in China to construct cyberinfrastructure to support protection and research on wild birds in plateau area. The e-Science application practices are also the first one applied in the national nature reserve in China.
  • Resources,Environmental and Economic Patterns and Sustainable Development Modes of Silk Road Economic Belt

    Resources,Environmental and Economic Patterns and Sustainable Development Modes of Silk Road Economic Belt

    The lecture summarizes the key scientific issues for the sustainable development in Silk Road Economic Belt and analyzes the distribution pattern of resources, ecological environment, society and economy, and holds that it is conducive to Silk Road countries to carry out Omni-directional and multi-level economic cooperation. Then the lecture discusses main modes and paths of sustainable economic development for Silk Road Economic Belt: Resource cooperation mode,Ecological civilization mode, Regional economic integration mode, Transportation economic belt mode, International tourism economic zone mode. Finally, the article puts forward several action projects.
  • Assessment

    Assessment

    Higher engineering education evaluation indicators system, college and professional ranking, undergraduate and graduate evaluation,etc.
  • Accreditation

    Accreditation

    Certification rules issued by national and international engineering education certification organizations, certification standards, accredited institutions and professional directories,etc.
  • Academecs trends

    Academecs trends

    The academic problems, reform, development and approaches of higher engineering education in developed and developing countries,etc.
  • Temperature data set in 1980-2010 years between China,Russia and Mongolia

    Temperature data set in 1980-2010 years between China,Russia and Mongolia

    The data set is average temperature interpolation data for China, Russian, Mongolia from 1980 to 2010, is based on the NCDC gsod global temperature data set http://www.ncdc.noaa.gov, and through spatial interpolation. The spatial resolution of the data for 1KM, a single band coverage data format, respectively. The temperature data during 1980-2010 year.
  • Precipitation data set for 1980-2010 years in China, Russia and Mongolia

    Precipitation data set for 1980-2010 years in China, Russia and Mongolia

    This data set is the average annual precipitation interpolation data of China, Russia and Mongolia 1980-2010 years, according to the NCDC gsod global precipitation data set http://www.ncdc.noaa.gov, and the spatial interpolation.
  • Surface vegetation cover data in Mongolia Plateau

    Surface vegetation cover data in Mongolia Plateau

    This data set in 1981 -1999 NDVI-PathFinder and 2000 -2012 MODIS data set based on vegetation index data set, two pixel model and vegetation index based on the data were retrieved from the data of Mongolia Plateau vegetation coverage in 1981 -2012 set. This data set provides the surface vegetation cover of 1981-2012 year in Mongolia plateau from 4-10 to 1981-2012. The overall accuracy of the data set is 75%.
  • MODIS vegetation index data of Mongolia plateau (2000-2012)

    MODIS vegetation index data of Mongolia plateau (2000-2012)

    This data set using the sinusoidal projection and 16 days of synthetic data, the spatial resolution of 250m, improve the NDVI observation of low saturation point, calculated on the basis of BRDF data, and a variety of mask processing (water, cloud, aerosol, cloud and shadow), helps to carry out the data analysis of the long-term dynamic assimilation and vegetation, and also can be used for detecting vegetation status, biological chemistry, water cycle and global and regional climate research.
  • MODIS enhanced vegetation index (2000-2012) in Mongolia Plateau

    MODIS enhanced vegetation index (2000-2012) in Mongolia Plateau

    This data set using the sinusoidal projection and 16 days of synthetic data, extraction of EVI, but also the full consideration of the atmospheric correction problems, the calculation is based on BRDF correction data, and a variety of mask processing. Compared to the NDVI EVI time series seasonal time series is more obvious, can better reflect the seasonal variation characteristics of high vegetation covered area, and there is little drop phenomenon, time series curve was smooth.
  • NDVI Vegetation time series data (1998-2012) in Mongolia Plateau

    NDVI Vegetation time series data (1998-2012) in Mongolia Plateau

    The data set provides the Mongolia plateau SPOT 10 days synthetic NDVI raster data with a resolution of 1000 meters, the coordinates of type WGS-84, projection using Albers projection.
  • Mongolia plateau land cover data (2009)

    Mongolia plateau land cover data (2009)

    The original data set is the MODIS Collection 5 data set produced by the Boston University. The data set, projection system and data format conversion of MCD12Q1 products using the MODIS reprojection tool MRT, and land_cover_type_1 data extraction layer, data classification system transformation, using resampling techniques covering raster data resolution are obtained for 500m resolution of the 2009 Mongolia plateau land. The overall accuracy of the data is about 75%, and the accuracy of different land cover types is different.
  • Mongolia plateau land cover data (2005)

    Mongolia plateau land cover data (2005)

    The original data set is the MODIS Collection 5 data set produced by the Boston University. The data set, projection system and data format conversion of MCD12Q1 products using the MODIS reprojection tool MRT, and land_cover_type_1 data extraction layer, data classification system transformation, using resampling techniques covering raster data resolution are obtained for 500m resolution of the 2005 Mongolia plateau land. The overall accuracy of the data is about 75%, and the accuracy of different land cover types is different.
  • Mongolia plateau land cover data (2001)

    Mongolia plateau land cover data (2001)

    The original data set is the MODIS Collection 5 data set produced by the Boston University. The data set, projection system and data format conversion of MCD12Q1 products using the MODIS reprojection tool MRT, and land_cover_type_1 data extraction layer, data classification system transformation, using resampling techniques covering raster data resolution are obtained for 500m resolution of the 2001 Mongolia plateau land. The overall accuracy of the data is about 75%, and the accuracy of different land cover types is different.
  • Intelligent City Events

    Intelligent City Events

    Events information on Intelligent City and Urban Planning collected from global institutes and universities.
  • Intelligent City News

    Intelligent City News

    News on Intelligent City and Urban Planning collected from major institutes' websites.
  • Data sources for multi Engineering disciplines

    Data sources for multi Engineering disciplines

    15 major engineering desciplines are picked out with 54 types of engineering data and 104 data sources. The network relationship of data flows among those 15 engineering desciplines is listed.
  • Global City Data_Social&Economy&Environment

    Global City Data_Social&Economy&Environment

    The data set is consisted of 26 indicators of 1262 global cities, indicating these cities' social, economic and environmental development.
  • Best Practices of Global Smart Cities

    Best Practices of Global Smart Cities

    Excellent cases done by cities around the world
  • 1 Month Taxi Data_NY

    1 Month Taxi Data_NY

    The yellow and green taxi trip records of New York City include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts. Time period: the whole month of January 2016.
  • Air Quality Data

    Air Quality Data

    ICity collected major Chinese cities' air quality data in the year 2016. Key indicators include AQI, PM2.5, PM10, CO, NO2, O3, etc.
  • International Engineering Sciences Symposium

    International Engineering Sciences Symposium

    Provide latest international engineering sciences symposium list
  • Global Engineering Experts

    Global Engineering Experts

    Collecting of global engineering expert information
  • Nepal basic national information database

    Nepal basic national information database

    Including Nepal based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Water Quality Data

    Water Quality Data

    ICity collected water quality data of hydrological monitoring stations along China's main water bodies since year 2004.
  • Thailand basic national information database

    Thailand basic national information database

    Including Thailand based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Kazakhstan basic national information database

    Kazakhstan basic national information database

    Including Kazakhstan based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Uzbekistan basic national information database

    Uzbekistan basic national information database

    Including Uzbekistan based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Turkmenistan basic national information database

    Turkmenistan basic national information database

    Including Turkmenistan based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Tajikistan basic national information database

    Tajikistan basic national information database

    Including Tajikistan based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • India basic national information database

    India basic national information database

    Including India based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Bangladesh basic national information database

    Bangladesh basic national information database

    Including Bangladesh based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Bhutan basic national information database

    Bhutan basic national information database

    Including Bhutan based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Burma basic national information database

    Burma basic national information database

    Including Burma based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Scholar's Network in Urban Planning Discipline

    Scholar's Network in Urban Planning Discipline

    Based on 2044 scholars of Urban Planning from 289 universities around the world, ICity Center collected over 80,000 academic publications. Through Network analysis, a global network of Urban Planning scholars can be found.
  • Laos basic national information database

    Laos basic national information database

    Including the basic situation of the Lao National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Vietnam basic national information database

    Vietnam basic national information database

    Including the basic national geographic data of Vietnam. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Kampuchea basic national information database

    Kampuchea basic national information database

    Including Kampuchea based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Philippines basic national information database

    Philippines basic national information database

    Including Philippines based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Population and Environment Featured Database

    Population and Environment Featured Database

    Collecting content to population, environment and development as the core, effectively reveal the national profile for regional sustainable development research, government management decision-making and the public to provide data services.
  • Industrial Economics Featured Database

    Industrial Economics Featured Database

    Collecting the basic situation, history, organization, development and business strategy, core business, SWOT report and other basic information of the world top 500 enterprises in the last five years, so as to understand the advantages and disadvantages of well-known enterprises.
  • Polices and Regulations Featured Database

    Polices and Regulations Featured Database

    Collecting a number of technical standards on information technology, energy and power, as well as some“the Belt and Road Initiatives”counties’ national laws and regulations, political system, international relations.
  • Union Message Featured Database

    Union Message Featured Database

    The National Report helps readers to keep track of the major events in the global market and to determine the impact of the event in the short to medium term. Each National Report will conduct a comprehensive and in-depth analysis of the main events in a country or region.
  • Education of Science Featured Database

    Education of Science Featured Database

    Collecting Universities Alliance of the New Silk Road of science and technology published literature and some foreign language resources for use.
  • History and Culture Featured Database

    History and Culture Featured Database

    Collecting electronic resources related to regional political, economic, cultural, developmental strategies and political research related to“the Belt and Road Initiatives” counties.
  • Pakistan basic national information database

    Pakistan basic national information database

    Including Pakistan based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Russian national information database

    Russian national information database

    Geographic data containing the Russian national conditions. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Inversion data set of Poyang Lake suspended matter concentration 2000-2013

    Inversion data set of Poyang Lake suspended matter concentration 2000-2013

    Use Poyang Lake area from 2009 to 2012 spring, summer, autumn and winter seasons continuously observed suspended solids concentration and the same period of MODIS Image product mod09a1 multi band linear regression analysis to obtain the inversion model of four seasons; based on these models, acquired Poyang Lake of suspended solids concentration from 2009 to 2012 by season . Furthermore, analyzes the Poyang Lake sexton concentrations of space-time distribution pattern and variation characteristics.
  • 2009-2012 inversion data set of chlorophyll a concentration in Poyang Lake

    2009-2012 inversion data set of chlorophyll a concentration in Poyang Lake

    This set of data made field spectral information collection and analysis, construct the spectral index, combining with the measured data of chlorophyll a concentration, using the least squares regression analysis method to get the sensitive band interval; the semi empirical method, the experience stage has been in Poyang Lake 2009-2012 chlorophyll estimation model for a concentration using MODIS data obtained in Poyang Lake from 2009 to January 2012, April, July and October the distributions of chlorophyll a concentration data.
  • Kyrgyzstan basic national information database

    Kyrgyzstan basic national information database

    Including Kyrgyzstan based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Mongolia basic national information database

    Mongolia basic national information database

    Including Mongolia based National Geographic Data. It includes three categories: basic national conditions, natural resources and political and economic data. Detailed classification: geographical location, administrative division, topography, soil, climate, rivers, lakes and the environment, land resources, water resources, forest resources, animal resources, plant resources, energy resources, mineral resources, non-metallic mineral resources, tourism resources, language, nationality, religion, festivals, political diplomacy, economy, science and technology, education, sports ,hospital bed density, etc.
  • Conferences and seminars

    Conferences and seminars

    Higher engineering education conferences and seminars of UNESCO, IFEE, ASEE, SEFI, WFEO and AEEA,etc.
  • Policy document

    Policy document

    The policy documents about the outstanding engineers education training plan issued by the Ministry of Education, Construction and Transport,etc.
  • Research literature

    Research literature

    Dissertations from engineering colleges and Journal papers about higher engineering education from IEEE, JEE, EJEE, etc.
  • Global Governments Open Dataset

    Global Governments Open Dataset

    Governments Open Dataset from US, UK, India, Singapore, Australia
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IKCEST News MORE
WU Zhiqiang gave consultancy instructions to the post-disaster recovery and reconstruction work in Changning, Yibin 2019-07-08
WU Zhiqiang gave consultancy instructions to the post-disaster recovery and reconstruction work in Changning, Yibin
On July 6th, CAE Member WU Zhiqiang, arrived in Yibin, Sichuan Province to do survey and give consultancy instructions to the post-disaster reconstruction planning work.
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The 3rd International Workshop for Disaster Risk Reduction Knowledge Service 2019-10-12
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Seminar on Intelligent City Knowledge Service System of International Knowledge Center for Engineering Sciences and Technology and IEID Sub-Forum on Green Low Carbon Technology and Industry were successfully held in Shanghai. 2019-10-11
Seminar on Intelligent City Knowledge Service System of International Knowledge Center for Engineering Sciences and Technology and IEID Sub-Forum on Green Low Carbon Technology and Industry were successfully held in Shanghai.
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The Sub-forum of the 2019 UASR Presidents’ Forum Organized by IKCEST 2019-10-10
The Sub-forum of the 2019 UASR Presidents’ Forum Organized by IKCEST
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The 2019 International Workshop of IKCEST Intelligent City Knowledge Service System held in Shanghai 2019-10-23
The 2019 International Workshop of IKCEST Intelligent City Knowledge Service System held in Shanghai
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International Training Workshop on Big Data for Developing Countries 2019 2019-09-22
International Training Workshop on Big Data for Developing Countries 2019
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2019 IKCEST & ICEE International Engineering Education Training Workshop held successfully at Tsinghua University 2019-08-01
2019 IKCEST & ICEE International Engineering Education Training Workshop held successfully at Tsinghua University
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