| 摘要: |
| 红树林-盐沼生态交错带是研究景观格局与生态过程、监测全球气候变化的重要区域，但其特有的动态性、过渡性和空间异质性给遥感监测带来了挑战。本研究以互花米草(Spartina alterniflora)入侵问题显著的广西丹兜海为研究区，基于卫星数据获取红树林-盐沼生态交错带的最佳观测时间窗口，指导无人机数据的采集，继而开展红树林-盐沼生态交错带的红树林和盐沼高精度制图。研究结果表明，密集时序Sentienl-2A/B卫星数据和时间序列谐波分析法重构的红树林和盐沼归一化植被指数能较好地指示最佳观测时间，即研究区植被的最佳观测时间是冬季，最佳观测时间组合是冬季和夏季。基于最佳观测时间组合的双时相卫星数据的随机森林分类方法能较好地抑制“同物异谱，异物同谱”导致的海岸带地物分类的错分和漏分以及卫星影像云遮档降低分类精度等问题。与拥有更多光谱波段的Sentienl-2A/B卫星数据相比，更高空间分辨率的可见光无人机数据在区分红树林、盐沼、光滩上有显著优势。 |
| 关键词: 红树林|盐沼|生态交错带|卫星遥感|无人机遥感|时间序列谐波分析法|密集时序 |
| DOI：10.3969/J.ISSN.2095-4972.20240220001 |
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| 基金项目:广东省促进经济高质量发展专项（GDNRC[2024]36）；自然资源部南海局科技发展基金（230206）；自然资源部海洋环境探测技术与应用重点实验室自主设立课题（MESTA-2020-C001，MESTA-2020-C006）；广东省林业局2024年度自然资源事务专项（广东省滨海湿地资源监测和生态价值评估） |
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| Combing satellite and UAV remote sensing to monitor a mangrove-salt marsh ecotone: a case study from Dandou Sea in Guangxi |
| DONG Di,HUANG Huamei,GAO Qing,ZHANG Shengpeng,LI Kang,WEI Zheng,SUN Yuchao |
| (South China Sea Development Research Institute，MNR，Guangzhou 510300，China;Technology Innovation Center for South China Sea Remote Sensing，Surveying and Mapping Collaborative Application，MNR，Guangzhou 510300，China;Key laboratory of Marine Environmental Survey Technology and Application，Guangzhou 510300，China) |
| Abstract: |
| 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. |
| Key words: mangrove|salt marsh|ecotone|satellite remote sensing|UAV remote sensing|harmonic analysis of time series|dense time series |
