Mapping the number of mangrove trees in the Guangdong-Hong Kong-Macao Greater Bay Area

被引:2
|
作者
Liu, Tang [1 ,3 ]
Zhou, Benjamin J. [2 ]
Jiang, Hou [3 ]
Yao, Ling [3 ]
机构
[1] China Univ Geosci Beijing, Beijing 100083, Peoples R China
[2] Int Sch Beijing, AnHua St, Beijing, Peoples R China
[3] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
关键词
Mangroves; Tree counting; Deep learning; Remote sensing; CHINA; CLASSIFICATION;
D O I
10.1016/j.marpolbul.2023.115658
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Mangroves are vital components of coastal ecosystems. Due to the complex canopy morphology and dense distribution of mangroves, it is challenging to accurately estimate the density based on satellite data. In this study, a density regression-based mangrove mapping network is proposed. The network can capture the multiscale characteristics of mangroves through the combination of an attention mechanism and a parallel segmentation path, and its performance is better than existing methods. We then apply it to mapping the Greater Bay Area (GBA) the number of mangrove trees. The results show about 2.55 million mangrove trees in the GBA, with an average density of 782 trees per hectare. The tree number of mangroves on the beach is significantly higher than those distributed along the riverbank. This study is the first to achieve mangrove tree count mapping, opening up new prospects for applying satellite-based mangrove monitoring.
引用
收藏
页数:14
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