Implementing Geographic Information System (GIS) tools: Algorithm and Quantum Geographic Information System (QGIS) plugin for automatic detection of riverbed forms.

This paper introduces the Sandbar Detector plugin for Quantum Geographic Information System (QGIS), designed to streamline the detection and analysis of riverbed forms, previously hindered by time-consuming manual methods requiring extensive expertise in remote sensing and Geographic Information System (GIS). The Sandbar Detector plugin, developed in Python, leverages the Sentinel Water Mask (SWM), a reliable remote sensing water index, for precise differentiation between water and land. By integrating SWM with QGIS, the plugin utilises high-resolution data from Sentinel-2 satellites, offering a robust tool for environmental analysis.