Datasets
315 Results
  • Kenli County Salinization Data 2014
    The data source for this dataset is USGS Landsat 8 OLI data. The spatial resolution is 30 meters, and after image processing such as radiometric calibration and atmospheric correction, the inversion data of the Kenli County in 2014 was obtained.
    Date: 02 January, 2020
    Source: Disaster Risk Reduction Knowledge Service
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  • Global monthly burned area from 1997 to 2016
    This dataset provides global estimates of monthly burned area at 0.25-degree x 0.25-degree for 1997 to 2016 in HDF .hdf format GFED4. Emissions data are available for carbon C, dry matter DM, carbon dioxide CO2, carbon monoxide CO, methane CH4, hydrogen H2, nitrous oxide N2O, nitrogen oxides NOx, non-methane hydrocarbons NMHC, organic carbon OC, black carbon BC, particulate matter less than 2.5 microns PM2.5, total particulate matter TPM, and sulfur dioxide SO2 among others. These data are yearly totals by region, globally, and by fire source for each region.
    Date: 02 January, 2020
    Source: Disaster Risk Reduction Knowledge Service
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  • 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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