The data set has the characteristics of high coverage, good timeliness (2020) and high resolution (10m). Taking Jinghe River Basin as the research area, the land use data processed by sentry 2 remote sensing image based on machine learning method is extracted, which is divided into nine categories (water body, forest land, grassland, submerged vegetation, cultivated land, shrub, building, bare land and cloud).
The data comes from https://livingatlas.arcgis.com/landcover/ .
Based on the remote sensing image of ESA sentry 2 with a resolution of 10 meters. Obtain 9 types of land use data in 2020 through machine learning;
Taking the Jinghe River Basin as the research area, the land use data of Jinghe River basin with a spatial resolution of 10 meters in 2020 are extracted by mask.
Good data quality.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.ncdc.JRiver.db1973.2022
10.12072/ncdc.JRiver.db1973.2022
