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- W2988948686 abstract "The extraction of urban impervious surface information plays a key role in the studies of urbanization and its related environmental issues. Optical and SAR remote sensing provides complementary information to improve the accuracy of impervious mapping. However, the fusing of information acquired by different sensors is challenging. Optical and SAR features have distinct characteristics, and require different classification strategy and classification types. In this study, a strategy of fusing multi-spectral optical and polarimetric SAR data at decision-level is proposed. Features are extracted from optical and SAR data, then staked auto-encoder is applied to achieve the land use and land cover classification separately. D-S evidence theory is used to fuse the classification result and the imperious surface map is derived. The experiment was conducted in a highly complex urban area of Hong Kong and the results proves the soundness of the method." @default.
- W2988948686 created "2019-11-22" @default.
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- W2988948686 date "2019-07-01" @default.
- W2988948686 modified "2023-09-25" @default.
- W2988948686 title "Mapping urban impervious surfaces by fusing optical and SAR data at decision level" @default.
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- W2988948686 doi "https://doi.org/10.1109/igarss.2019.8898039" @default.
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