The 30 m annual land cover datasets and its dynamics in China from 1985 to 2024

<p>Using 335,709 Landsat images on the Google Earth Engine, we built the&nbsp;first Landsat-derived annual land cover product of China (CLCD) from 1985 to 2019. 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.&nbsp;</p> <p>"*_albert.tif"&nbsp;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".</p> <p>CLCD in 2024 is now available.</p> <p>1. Given that the&nbsp;USGS no longer maintains the Landsat Collection 1 data, we are now using&nbsp;the <a href="https://www.usgs.gov/landsat-missions/landsat-collection-2">Collection 2</a> SR data to update the CLCD.</p> <p>2. All files in this version have been exported as Cloud Optimized GeoTIFF&nbsp;for more efficient processing on the cloud. Please check <a href="https://www.cogeo.org/">here</a> for more details.</p> <p>3. Internal overviews and color tables are built into each file to&nbsp;speed up software loading and rendering.</p>