A Tidal Flat Wetlands Delineation and Classification Method for High-Resolution Imagery

• Published in: ISPRS international journal of geo-information Vol. 10; no. 7; p. 451
• Main Authors: Pan, Hong, Jia, Yonghong, Zhao, Dawei, Xiu, Tianyu, Duan, Fuzhi
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2021
• Subjects: Algorithms; Classification; Decision trees; Deep learning; Delineation; Ecological function; feature descriptor; High resolution; high-resolution images; Image classification; Image resolution; Imagery; Methods; Monitoring; Object recognition; Offshore; Pollution; Remote sensing; Resolution; Seawater; shoreline prediction; Shorelines; tidal correction; tidal flat wetlands; Tidal flats; Vegetation; Wetlands
• ISSN: 2220-9964; 2220-9964
• DOI: 10.3390/ijgi10070451

As an important part of coastal wetlands, tidal flat wetlands provide various significant ecological functions. Due to offshore pollution and unreasonable utilization, tidal flats have been increasingly threatened and degraded. Therefore, it is necessary to protect and restore this important wetland by monitoring its distribution. Considering the multiple sizes of research objects, remote sensing images with high resolutions have unique resolution advantages to support the extraction of tidal flat wetlands for subsequent monitoring. The purpose of this study is to propose and evaluate a tidal flat wetland delineation and classification method from high-resolution images. First, remote sensing features and geographical buffers are used to establish a decision tree for initial classification. Next, a natural shoreline prediction algorithm is designed to refine the range of the tidal flat wetland. Then, a range and standard deviation descriptor is constructed to extract the rock marine shore, a category of tidal flat wetlands. A geographical analysis method is considered to distinguish the other two categories of tidal flat wetlands. Finally, a tidal correction strategy is introduced to regulate the borderline of tidal flat wetlands to conform to the actual situation. The performance of each step was evaluated, and the results of the proposed method were compared with existing available methods. The results show that the overall accuracy of the proposed method mostly exceeded 92% (all higher than 88%). Due to the integration and the performance superiority compared to existing available methods, the proposed method is applicable in practice and has already been applied during the construction project of Hengqin Island in China.