A 10-m resolution impervious surface area map for the greater Mekong subregion from multisource remote sensing images

Here, the 2016-2022 impervious surface area map exclusively for the greater Mekong subregion is prepared. We present a novel machine-learning framework implemented on the Google Earth Engine platform that merges Sentinel-1 Synthetic Aperture Radar images and Sentinel-2 Multispectral images to extract impervious surface area. Furthermore, we also introduce a training sample migration strategy that eliminates the need for collecting additional training samples and automates multi-temporal impervious surface area mapping. Finally, we perform a quantitative assessment with validation samples interpreted from Google Earth. Results show that the overall accuracy and kappa coefficient of the final impervious surface area maps range from 93.67% to 93.75% and 0.872 to 0.873, respectively. This dataset provides comprehensive measurements of impervious surface coverage and configuration that will help to inform urban ecological studies. <br> The impervious surface map includes three sets of files: (1) the map data in GEOTIFF format, (2) the distribution of the tiles in shapefile format, and (3) the thumbnails of the dataset in JPEG format. This dataset can be viewed and processed with geographic information and remote sensing software, programming packages, and cloud platforms such as ArcGIS, QGIS, ENVI, GDAL, and GEE.