Surface water monitoring from 1984 to 2021 based on Landsat time-series images and Google Earth Engine.

ABSTRACT: Dynamic monitoring of surface water bodies is essential for understanding global climate change and the impact of human activities on water resources. Satellite remote sensing is characterized by large-scale monitoring, timely updates, and simplicity, and it has become an important means of obtaining the distribution of surface water bodies. This study is based on a long time-series Landsat satellite images and the Google Earth Engine (GEE) platform, focusing on Anhui Province in China, and proposes a method for extracting surface water that combines water indices, Bias-Corrected Fuzzy Clustering Method (BCFCM), and OTSU threshold segmentation. The spatial distribution of surface water in Anhui Province was obtained from 1984 to 2021, and further analysis was conducted on the spatiotempora

SUBMITTER: Zhao B 

PROVIDER: S-EPMC11388736 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature