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

ABSTRACT: High-resolution and multi-temporal impervious surface area maps are crucial for capturing rapidly developing urbanization patterns. However, the currently available relevant maps for the greater Mekong subregion suffer from coarse resolution and low accuracy. Addressing this issue, our study focuses on the development of accurate impervious surface area maps at 10-m resolution for this region for the period 2016-2022. To accomplish this, we present a new 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 surfaces. Furthermore, we also introduce a training sample migration strategy that eliminates the collection of additional training samples and automates

SUBMITTER: Sun G 

PROVIDER: S-EPMC10492804 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature