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250 m Raster Dataset of Vegetation Classification in the Xizang Autonomous Region Based on FY-3D NDVI (2020)

ZHANG Lei1ZHOU Guangsheng*2REN Hongrui1LV Xiaomin2
1 Department of Geomatics,Taiyuan University of Technology,Taiyuan030024,China2 Chinese Academy of Meteorological Sciences,Beijing100081,China


Published:Apr. 2024

Visitors:697       Data Files Downloaded:16      
Data Downloaded:43.84 MB      Citations:

Key Words:

Xizang Autonomous Region,GEE,FY satellite,vegetation map,Random Forest


Utilizing the Google Earth Engine (GEE) platform and the Random Forest (RF) algorithm, the authors developed the 250 m raster dataset of vegetation classification in the Xizang Autonomous Region (2020), incorporating terrain, climate, and FY-3D NDVI data. The classification system includes 12 types, including broad-leaved forest, coniferous forest, coniferous and broad-leaved mixed forest, scrub, alpine meadow, alpine grassland, alpine vegetation, alpine desert, cultivated vegetation, wetland, water, and other. The results indicate that in 2020, the areas covered by each vegetation type in the Xizang Autonomous Region were as follows: broad-leaved forest covered 49,039.6 km², coniferous forest 49,870.5 km², coniferous and broad-leaved mixed forest 7,163.1 km², scrub 10,386.3 km², alpine meadow 292,323.9 km², alpine grassland 404,775.0 km², alpine vegetation 136,594.9 km², alpine desert 154,924.0 km², cultivated vegetation 3,834.1 km², wetland 4,259.3 km², water 32,169.5 km², and other 63,814.6 km². The data has an overall accuracy of 81.5% and a Kappa coefficient of 0.79. The dataset includes: (1) vegetation classification system table, and (2) vegetation distribution data at 250 m resolution in 2020. The dataset is archived in .xlsx and .tif formats, and consists of 2 data files with data size of 3.16 MB (compressed to one single file with 2.73 MB).

Foundation Item:

Ministry of Science and Technology of P. R. China (2019QZKK0106)

Data Citation:

ZHANG Lei, ZHOU Guangsheng*, REN Hongrui, LV Xiaomin. 250 m Raster Dataset of Vegetation Classification in the Xizang Autonomous Region Based on FY-3D NDVI (2020)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024.


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Data Product:

ID Data Name Data Size Operation
1 VegetationXizang2020.rar 2805.77KB