Agreement Analysis and Accuracy Assessment of Multiple Mangrove Datasets in Guangxi Beibu Gulf and Guangdong-Hong Kong-Macau Greater Bay, China, for 2000–2020

Autor: Zhijie Xiao, Weiguo Jiang, Zhifeng Wu, Ziyan Ling, Yawen Deng, Ze Zhang, Kaifeng Peng
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3438-3451 (2024)
Druh dokumentu: article
ISSN: 2151-1535
DOI: 10.1109/JSTARS.2024.3353251
Popis: Accurate and reliable mangrove datasets are essential for the protection and management of mangrove ecosystems. Therefore, the evaluation of the current mangrove datasets and understanding the differences among them are critical. This study takes the Guangxi Beibu Gulf (GBG) and Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the study areas and analyzes the agreement and accuracy of eight mangrove datasets from 2000 to 2020 using area comparison, spatial agreement analysis, and absolute accuracy evaluation. The results show that; 1) significant differences exist in mangrove area and spatial distribution among the different mangrove datasets, with the percentage of high agreement areas ranging from 10% to 42%. 2) The overall accuracy of the evaluated mangrove datasets ranges from 56.2% to 95.6%, and the classification accuracy of mangrove datasets in inland areas is lower than the overall level. 3) There are regional differences in the quality of mangrove datasets, with the agreement and accuracy of mangrove datasets in the GBG being greater than those in the GBA. 4) Fine-scale mangrove mapping based on high-resolution remote sensing images, such as Sentinel, and global mangrove mapping based on the Google Earth Engine (GEE) cloud platform should be emphasized in the future. The findings of this study can provide guidance for data users to select appropriate mangrove datasets and a reference for future mangrove mapping research.
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