Datasets
176 Results
  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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  • 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.
    Date: 11 October, 2019
    Source: Disaster Risk Reduction Knowledge Service
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