Land Cover Analysis in the Yangtze River Basin for Detection of Wetland Agriculture and Urban Dynamics in Wuhan Area (China)

Abstract This study presents environmental analysis of the Yangtze River Basin, Wuhan region of central China, performed using machine learning (ML) methods of Remote Sensing (RS) data classification. The workflow is performed using Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS) scripting software for processing Landsat images by two approaches: unsupervised clustering and supervised ML algorithms. Six Landsat images were taken biennially in autumn from 2013 to 2023 to detect wetland changes in the Wuhan area. This article demonstrates the application of ML in GIS for analysis of landscape dynamics to detect changes in riverine and lacustrine areas around the Yangtze River.