基于Sentinel-1和Sentinel-2影像的洪泽湖国家湿地公园水生植被信息提取OA北大核心CSTPCD

[Objective]The objective of this study was to explore the extraction of spatio-temporal distribution of aquatic vegetation in lake wetlands using Sentinel-1 and Sentinel-2 data.[Method]Hongze Lake National Wetland Park was chosen as the research area.Based on the combination of Sentinel-2 MSI images and Sentinel-1 SAR images,the object-oriented image analysis was used.The feature set was constructed by using EVSI,NDVI,SR feature index and contextual features between objects,as well as differences in the backscatter coefficients of the SAR images corresponding to differences in the height of the emergent vegetation types.A decision-tree model was established at the object level to classify the wetland,and the spatio-temporal distribution of the aquatic vegetation and the emergent vegetation in the Hongze Lake National Wetland Park was acquired.[Result]The classification accuracy and the Kappa coefficient of aquatic vegetation were observed to be 89％and 0.85,respectively,and that of the emergent vegetation was 85.2％and 0.76,respectively.The results showed that,compared with the results of the pixel-based analysis method,the accuracy of object-based image analysis was higher.The wetland aquatic vegetation was dominated by submerged and emergent vegetation;among the emergent vegetation,lotus leaves and reeds were dominant.[Conclusion]The methods proposed in this study were feasible,and the results could provide a scientific basis for managers and planners of wetlands.