Spatiotemporal Analysis of Water Body in the Chongming Island Region over the Past Decade Based on the ISUNet Model

Abstract

Chongming Island and its surrounding areas are highly significant coastal regions in China. However, the regions undergo continuous changes owing to various factors, such as the sedimentation from the Yangtze River, human activities, and tidal movements. Chongming Island is part of the Yangtze River Delta, which is one of the most economically developed regions in China. Studying the water body changes in this area is of great importance for decision making in water resource conservation, coastal resource management, and ecological environmental protection. In this study, we propose an improved ISUNet model by enhancing the skip-connection operations in the traditional UNet architecture. We extracted and analyzed the water bodies in Chongming Island and its surrounding areas from 2013 to 2022, providing a detailed spatiotemporal analysis of the water body area over the years. The results indicate that the water body area in the study area has decreased by 267.8 km2 over the past decade, showing a gradually fluctuating downward trend with an average annual reduction of nearly 27 km2. The analysis suggests that the reduction in the water body area is mainly attributed to sedimentation near river channels and ports, the formation of sandbars owing to channel erosion, and the artificial construction of ports and coastal areas. The influencing factors include human activities and sedimentation from the Yangtze River Estuary. Specifically, human activities such as land reclamation, port construction, and aquaculture play a major role in causing changes in the area.

Keywords

• Chongming Island
• deep learning
• UNet model
• water body extraction
• spatiotemporal variation