Toward a better understanding of coastal salt marsh mapping: A case from China using dual-temporal images

作者：Chuanpeng Zhao, Mingming Jia, Zongming Wang, Dehua Mao, Yeqiao Wang · 发表于：Remote Sensing of Environment · 年份：2023 · DOI：10.1016/j.rse.2023.113664 · 被引用次数：66 · 研究领域：Remote Sensing in Agriculture、Remote Sensing and LiDAR Applications、Flood Risk Assessment and Management

Coastal salt marshes suffering from anthropogenic coastal development and sea level rise have attracted much attention because of their capacity for carbon sequestration and global climate change mitigation . Accurate mapping of coastal salt marshes is always the first step for their protection, management, and restoration. The inherent complexities of vegetation, dynamics of tides, and anthropogenic disturbances pose challenges for remote sensing-based approaches. Existing studies have utilized phenology information and various black-box algorithms to reduce misclassifications. However, the approaches with dual-temporal images containing phenology information have suffered from inefficiency; the misclassifications have been objectively post-processed rather than considered in the method design, and the tacit knowledge of the trained black-box models has not been revealed. To address the above issues, we proposed a new approach with solid improvements in dual-temporal image construction, misclassification processing, and tacit knowledge analysis, including an efficient method to synthesize dual-temporal images based on the common divisor of the green-up season or senescence season resulting from latitudinal gradients in narrow coastal areas of China, a detailed classification scheme by interpretation of iteratively collected samples, and a key decision rule approximating the trained model. We applied the approach to Sentinel-1/2 images and DEM data, thus deriving a 10-m resol...