Integrating Remote Sensing and Field Data to Quantify Mangrove Biomass Carbon Hotspots and Protection Gaps in Guangdong, China

Mangroves are important blue carbon coastal ecosystems and play a crucial role in mitigating global climate change. However, fine spatial patterns of mangrove biomass carbon hotspots and protection gaps in Guangdong have not been quantified. In this study, we mapped mangrove biomass carbon by integrating Sentinel-2 satellite imagery and field survey data from Guangdong’s coastlines acquired in 2023 for the first time. Using the Getis-Ord Gi* spatial statistic method, we identified the mangrove biomass carbon hotspots and highlighted protection gaps in mangrove conservation. The total mangrove biomass carbon of Guangdong was estimated to be 1,209,305.68 Mg C (with a mean density of 80.56 Mg C/ha), with Zhanjiang containing the highest carbon stock, accounting for over half of the total. Nature reserves supported higher mean biomass carbon (83.03 Mg C/ha), compared with areas outside nature reserves (77.99 Mg C/ha), underscoring their important role in enhancing mangrove carbon storage. The overlapping area between the mangrove biomass carbon stock hotspot areas and the nature reserves is 71.62 km2, accounting for 51.13% of the total hotspot area. In terms of mangrove biomass carbon stocks, the main protection gaps in Guangdong are distributed in Anpu Gang, the region south of Zhanjiang, Shuidong Harbor, Pearl River Estuary, Kaozhou Yang, and Yifengxi Port. Our findings reveal the spatial heterogeneity of mangrove carbon stocks in Guangdong and provide novel insights for optimizing mangrove management and spatial planning of nature reserves for conservation and restoration.

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Publication Details

Journal
Forests
Published
2025-10-21
DOI
https://doi.org/10.3390/f16101612
Primary Topic
Coastal wetland ecosystem dynamics
Type
article
Field-Weighted Citation Impact
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article

Integrating Remote Sensing and Field Data to Quantify Mangrove Biomass Carbon Hotspots and Protection Gaps in Guangdong, China

Huamei Huang, Di Dong, Shengpeng Zhang, Qing Gao et al.
Forests
Coastal wetland ecosystem dynamics
article

Integrating Remote Sensing and Field Data to Quantify Mangrove Biomass Carbon Hotspots and Protection Gaps in Guangdong, China

Huamei Huang, Di Dong, Shengpeng Zhang, Qing Gao, Ran Yan, Kang Li
article en

Abstract

Mangroves are important blue carbon coastal ecosystems and play a crucial role in mitigating global climate change. However, fine spatial patterns of mangrove biomass carbon hotspots and protection gaps in Guangdong have not been quantified. In this study, we mapped mangrove biomass carbon by integrating Sentinel-2 satellite imagery and field survey data from Guangdong’s coastlines acquired in 2023 for the first time. Using the Getis-Ord Gi* spatial statistic method, we identified the mangrove biomass carbon hotspots and highlighted protection gaps in mangrove conservation. The total mangrove biomass carbon of Guangdong was estimated to be 1,209,305.68 Mg C (with a mean density of 80.56 Mg C/ha), with Zhanjiang containing the highest carbon stock, accounting for over half of the total. Nature reserves supported higher mean biomass carbon (83.03 Mg C/ha), compared with areas outside nature reserves (77.99 Mg C/ha), underscoring their important role in enhancing mangrove carbon storage. The overlapping area between the mangrove biomass carbon stock hotspot areas and the nature reserves is 71.62 km2, accounting for 51.13% of the total hotspot area. In terms of mangrove biomass carbon stocks, the main protection gaps in Guangdong are distributed in Anpu Gang, the region south of Zhanjiang, Shuidong Harbor, Pearl River Estuary, Kaozhou Yang, and Yifengxi Port. Our findings reveal the spatial heterogeneity of mangrove carbon stocks in Guangdong and provide novel insights for optimizing mangrove management and spatial planning of nature reserves for conservation and restoration.

ForestsVol. 16(10)
Sun Yat-sen University (CN), Ministry of Natural Resources (CN), Guangzhou Marine Geological Survey (CN), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN), Ministry of Water Resources of the People's Republic of China (CN)
Openalex Percentile: Top 71%
Coastal wetland ecosystem dynamics
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