Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning
As a unique land-sea transitional wetland, mangroves possess high ecosystem service value. Monitoring mangroves in cross-border areas is crucial for shaping bilateral protection policies and guiding effective management decisions. This study examines the spatio-temporal dynamics of mangroves in the...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25000421 |
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| author | Wenna Gao Chunyan Lu Nuocheng Yang Yuqi Wu Kexin Wu Zhangjuan Chen |
| author_facet | Wenna Gao Chunyan Lu Nuocheng Yang Yuqi Wu Kexin Wu Zhangjuan Chen |
| author_sort | Wenna Gao |
| collection | DOAJ |
| description | As a unique land-sea transitional wetland, mangroves possess high ecosystem service value. Monitoring mangroves in cross-border areas is crucial for shaping bilateral protection policies and guiding effective management decisions. This study examines the spatio-temporal dynamics of mangroves in the Beibu Gulf, situated in the China-Vietnam cross-border region, utilizing long-term Landsat imagery and an object-oriented deep learning classification technique from 1991 to 2021. Combining land cover change, landscape indices, and spatial analysis, the spatio-temporal dynamics of mangroves were quantitatively evaluated. Results reveal that the object-oriented deep learning classification method significantly enhances mapping accuracy and integrality of the classification results. During 1991−2021, the mangrove area in the Beibu Gulf coastal zone (BGCZ) increased by 92.11 km2, with annual increases of 0.82 km2 in the China part and 2.25 km2 in the Vietnam part. Mangroves connectivity improved in both the China and Vietnam parts, though the degree of disturbance was more pronounced in the Vietnam part compared to the China part. Mangrove dynamics are influenced by numerous factors, with aquaculture being the primary cause of mangrove fragmentation in the BGCZ. Varied management mechanisms and coastal zone development models in China and Vietnam have exerted influence on the dynamic evolution of mangroves. This study offers a significant scientific foundation for future cross-border mangrove conservation and management. |
| format | Article |
| id | doaj-art-0eff1fffc4ca43b4b9d4bd1d80e0e6b1 |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-0eff1fffc4ca43b4b9d4bd1d80e0e6b12025-01-31T05:10:54ZengElsevierEcological Indicators1470-160X2025-01-01170113113Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learningWenna Gao0Chunyan Lu1Nuocheng Yang2Yuqi Wu3Kexin Wu4Zhangjuan Chen5College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002 China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou 350002 ChinaCollege of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002 China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou 350002 China; The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions, Wuyi University, Wuyishan 354300 China; Corresponding author.College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002 China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou 350002 ChinaCollege of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002 China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou 350002 ChinaCollege of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002 China; Key Laboratory of Smart Agriculture and Forestry (Fujian Agriculture and Forestry University), Fujian Province University, Fuzhou 350002 ChinaCollege of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002 ChinaAs a unique land-sea transitional wetland, mangroves possess high ecosystem service value. Monitoring mangroves in cross-border areas is crucial for shaping bilateral protection policies and guiding effective management decisions. This study examines the spatio-temporal dynamics of mangroves in the Beibu Gulf, situated in the China-Vietnam cross-border region, utilizing long-term Landsat imagery and an object-oriented deep learning classification technique from 1991 to 2021. Combining land cover change, landscape indices, and spatial analysis, the spatio-temporal dynamics of mangroves were quantitatively evaluated. Results reveal that the object-oriented deep learning classification method significantly enhances mapping accuracy and integrality of the classification results. During 1991−2021, the mangrove area in the Beibu Gulf coastal zone (BGCZ) increased by 92.11 km2, with annual increases of 0.82 km2 in the China part and 2.25 km2 in the Vietnam part. Mangroves connectivity improved in both the China and Vietnam parts, though the degree of disturbance was more pronounced in the Vietnam part compared to the China part. Mangrove dynamics are influenced by numerous factors, with aquaculture being the primary cause of mangrove fragmentation in the BGCZ. Varied management mechanisms and coastal zone development models in China and Vietnam have exerted influence on the dynamic evolution of mangroves. This study offers a significant scientific foundation for future cross-border mangrove conservation and management.http://www.sciencedirect.com/science/article/pii/S1470160X25000421China-Vietnam cross-borderObject-oriented deep learning classificationMangrove dynamicsLong-term remote sensing observationBeibu Gulf |
| spellingShingle | Wenna Gao Chunyan Lu Nuocheng Yang Yuqi Wu Kexin Wu Zhangjuan Chen Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning Ecological Indicators China-Vietnam cross-border Object-oriented deep learning classification Mangrove dynamics Long-term remote sensing observation Beibu Gulf |
| title | Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning |
| title_full | Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning |
| title_fullStr | Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning |
| title_full_unstemmed | Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning |
| title_short | Cross-border mangrove dynamics and management in the Beibu Gulf: Long-term remote sensing observation using object-oriented deep learning |
| title_sort | cross border mangrove dynamics and management in the beibu gulf long term remote sensing observation using object oriented deep learning |
| topic | China-Vietnam cross-border Object-oriented deep learning classification Mangrove dynamics Long-term remote sensing observation Beibu Gulf |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25000421 |
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