%0 Dataset
%T The 30 m annual land cover datasets and its dynamics in China from 1985 to 2022
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/9de270f3-b5ad-4e19-afc0-2531f3977f2f
%W NCDC
%R 10.5281/zenodo.8176941
%A None
%K Land cover;land cover dynamics;Landsat
%X Using 335,709 Landsat images on the Google Earth Engine, we built the first Landsat-derived annual land cover product of China (CLCD) from 1985 to 2022. We collected the training samples by combining stable samples extracted from China's Land-Use/Cover Datasets (CLUD), and visually-interpreted samples from satellite time-series data, Google Earth and Google Map. Several temporal metrics were constructed via all available Landsat data and fed to the random forest classifier to obtain classification results. A post-processing method incorporating spatial-temporal filtering and logical reasoning was further proposed to improve the spatial-temporal consistency of CLCD. "*_albert.tif" are projected files via a proj4 string "+proj=aea +lat_1=25 +lat_2=47 +lat_0=0 +lon_0=105 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs".CLCD in 2022 is now available. Given that the USGS no longer maintains the Landsat Collection 1 data, we are now using the Collection 2 SR data to update the CLCD. All files in this version have been exported as Cloud Optimized GeoTIFF for more efficient processing on the cloud. Please check https://www.cogeo.org/ for more details. Internal overviews and color tables are built into each file to speed up software loading and rendering.