The dataset is characterized by high coverage, good timeliness (2020), and high resolution (10 m). Taking the Weihe River Basin as the study area, the land use data processed by Sentinel 2 remote sensing imagery based on the machine learning method were extracted and classified into ten major categories (water bodies, trees, grasslands, submerged vegetation, crops, thickets/shrubs, built-up areas, bare ground, snow/ice, and cloud cover).
Data from https://livingatlas.arcgis.com/landcover/.
Based on ESA Sentinel 2 remote sensing imagery at 10-meter resolution. Ten categories of land-use data for the whole year of 2020 were acquired by machine learning methods.
Taking the Weihe River Basin as the study area, the mask extracted land use data with a spatial resolution of 10 meters in 2020 for the Weihe River Basin.
Data quality is good.
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CSTR:11738.11.ncdc.WRiver.2021.12
10.12072/ncdc.WRiver.db0014.2021