Datasets
245 Results
  • Forest type cover data with 10m spatial resolution of China2018
    This dataset is the forest type cover data with 10m spatial resolution of China 2018. Combining Landsat and sentinel-2 remote sensing images as data sources, the spectral and spatiotemporal feature sets of different forest types have been established. Using Landsat and time series harmonic analysis to establish a time feature set. Based on the spectral-temporal feature set, supported by reference data, the random forest recursive feature elimination algorithm is used to study and establish the main features of different regions. According to the spectral-spatial-temporal feature sets of different regions, four machine learning algorithms are used to establish a forest type classification model. Then, using the determined best-fitting model, a forest type map with a spatial resolution of 10 in Southeast China in 2018 was generated. The data format is TIF, the spatial range is Southeast China, and the time is 2018.
    Date: 30 September, 2021
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  • Heat wave disaster in China Pakistan Economic Corridor
    The basic data involved in this dataset is obtained from the NOAA website. According to 2000-2020 weather station data, night light data, GDP and other data, we obtain high-temperature heat wave vulnerability data, high-temperature heat wave exposure data, and high-temperature heat wave risk data, thereby obtaining high-temperature heat wave risk assessment data at ten-year intervals. The data can help scientific researchers and government agencies understand the overall situation of heat wave disasters in the China-Pakistan Economic Corridor and some measures to prevent heat wave disasters.
    Date: 30 September, 2021
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  • Surface disturbance trajectory of Karachi urban expansion of China-Pakistan Economic Corridor 2000-2020
    This data set is the surface disturbance trajectory of Karachi urban expansion of the China-Pakistan Economic Corridor from 2000 to 2020. It mainly records the expansion time of the urban built-up area. There are 9883 records in 1 .shp file. They are produced by the Institute of Geographical Sciences and Natural Resources Research of the Chinese Academy of Sciences and can be used for urban expansion studies to provide a basis for the urbanization research of Karachi, Pakistan.
    Date: 30 September, 2021
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  • Dataset of soil salinization in the lower Yellow River and coastal cities(2015-2020)
    This dataset is a dataset of temporal and spatial changes in salinization in the lower Yellow River and coastal cities from 2015 to 2020. It mainly records the spatial distribution of salinization in the lower reaches of the Yellow River and coastal cities, as well as the characteristics of temporal and spatial distribution. There are 2 vector files in total. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. And it can provide important basis for monitoring and prevention of land degradation disaster.
    Date: 30 September, 2021
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  • Islamabad 10m Sentinel Cloudless Quarterly Dataset 2017-2020
    This data set is a 10m Sentinel cloudless quarterly data set for Islamabad from 2017 to 2020, a total of 16 issues. The original data is the Sentinel ten-day data released by the Copernicus Data Center of ESA, after the cloudless algorithm, spatio-temporal filtering, and invalid threshold. It is obtained after cloud judgment, cloud removal, and data patching by removing and pixel-based median filtering. The data format is TIF format with a spatial resolution of 10 meters.
    Date: 30 September, 2021
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  • Land degradation and restoration data set in Mongolia from 2015 to 2020
    This data set is the land degradation and restoration data set in Mongolia from 2015 to 2020. It mainly records the types of land degradation and restoration, as well as the characteristics of spatial and temporal distribution, with a total of 3 vector files. They were collected and organized by the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. And it can provide important basis for monitoring and prevention of land degradation disaster.
    Date: 30 September, 2021
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  • Global Disaster Metadata Database
    The database contains metadata information related to various disaster data sets around the world.
    Date: 04 June, 2021
  • Rainstorm and Flood Disaster in Xi'an
    The main contents of the rainstorm and flood disaster in Xi'an are the heavy rainstorm and flood disasters since 1949, including the date of the rainstorm and flood in Xi'an, the degree of rainfall, the station, the max flood peak, etc.
    Date: 04 June, 2021
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  • Lightning Disaster in Xi'an
    The main contents of the Lightning Disaster in Xi'an are the lightning disasters since 1979, including the date of the lightning disaster in the city of Xi'an, the economic losses, the casualty, etc.
    Date: 04 June, 2021
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  • Hail Disaster in Xi'an
    The main contents of the hail disaster in Xi'an are the hail disasters since 1959, including the date of the hail disaster in the city of Xi'an, the hail diameter, the hail weight, the thickness of the hail on ground, the duration, etc.
    Date: 04 June, 2021
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