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DONG Di, HUANG Huamei, GAO Qing, ZHANG Shengpeng, LI Kang, WEI Zheng, SUN Yuchao. Combing satellite and UAV remote sensing to monitor a mangrove-salt marsh ecotone: a case study from Dandou Sea in Guangxi[J]. Journal of Applied Oceanography, 2025, 44(1): 167-176. DOI: 10.3969/J.ISSN.2095-4972.20240220001
Citation: DONG Di, HUANG Huamei, GAO Qing, ZHANG Shengpeng, LI Kang, WEI Zheng, SUN Yuchao. Combing satellite and UAV remote sensing to monitor a mangrove-salt marsh ecotone: a case study from Dandou Sea in Guangxi[J]. Journal of Applied Oceanography, 2025, 44(1): 167-176. DOI: 10.3969/J.ISSN.2095-4972.20240220001

Combing satellite and UAV remote sensing to monitor a mangrove-salt marsh ecotone: a case study from Dandou Sea in Guangxi

  • Mangrove-salt marsh ecological ecotone is an important region for landscape pattern and ecological process study, as well as global climate change monitoring. However, its unique dynamic and transitional nature and spatial heterogeneity pose challenges for ecotone remote sensing monitoring. Here, we take Dandou Sea as the study area where invasion of Spartina alterniflora is a severe problem. The best time window for ecotone observation was obtained based on satellite data, which guides the UAV data collection. Then we conducted high-precision mapping of mangroves and salt marshes in the study region. The mangrove and salt marsh NDVI time series reconstructed from the dense time series Sentienl-2A/B satellite data and time series harmonic analysis method can reflect the vegetation phenological changes, indicating that the best observation time in the study area is in winter, and the best observation time combination is winter and summer. The random forest classification method based on dual-temporal satellite data collected on the best observation time combination can better resolve questions, such as land cover misclassification and the omission caused by the phenomenon of same objects but different spectra, the different objects of same spectrum or the satellite imageries with clouds. Compared with the Sentienl-2A/B satellite data with more spectral bands, the UAV-based RGB imagery with higher spatial resolution presents more notable advantage in distinguishing mangroves, salt marshes and mud flats of the ecotone.
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