Sub-Pixel Surface Water Mapping for Heterogeneous Areas from Sentinel-2 Images: A Case Study in the Jinshui Basin, China
نویسندگان
چکیده
Mapping high-spatial-resolution surface water bodies in urban and suburban areas is crucial understanding the spatial distribution of water. Although Sentinel-2 images are popular mapping bodies, they impacted by mixed-pixel problem. Sub-pixel can predict finer-spatial-resolution maps from input remote sensing image reduce problem to a great extent. This study proposes sub-pixel method based on morphological dilation erosion operations Markov random field (DE_MRF) 2 m resolution map for heterogeneous regions imagery. DE_MRF first segments normalized difference index extract pixels then detects mixed using combined operations. For pixels, considers intra-pixel spectral variability extracting multiple endmembers land within local window generate fraction through unmixing. was evaluated Jinshui Basin, China. The results suggested that generated lower commission error rate compared comparison methods. Because intra-class variabilities unmixing, it better where different with distinct reflectance present.
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ژورنال
عنوان ژورنال: Water
سال: 2023
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w15081446