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- W2772950630 abstract "Landslides occur frequently and it is very meaningful to monitor them in disaster researches. Extracting the landslide from the high resolution satellite with fewer false changes is an important problem to be solved for remote sensing change detection research. In high spatial resolution and multi-temporal remote sensing images, landslides show significant differences with the background in both temporal and spatial neighborhoods, the knowledge of fusing temporal and spatial information is more favorable for landslide detection. NDVI (Normalized Difference Vegetable Index) and PanTex (built-up area presence index) features can reflect these changes in vegetable and built-up area respectively. Based on GF-1 CCD data and the change detection method of spatio-temporal context, the proposed method can detect the landslide area accurately by using NDVI and PanTex features." @default.
- W2772950630 created "2017-12-22" @default.
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- W2772950630 date "2017-07-01" @default.
- W2772950630 modified "2023-09-23" @default.
- W2772950630 title "Landslide change detection based on spatio-temporal context" @default.
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- W2772950630 doi "https://doi.org/10.1109/igarss.2017.8127147" @default.
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