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Landslide detection using probability regression,a case study of Wenchuan,northwest of Chengdu
Affiliation:1. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China;2. Key laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China;3. USDA Agricultural Research Service, Aerial Application Technology Research Unit, 3103 F & B Road, College Station, TX 77845, USA
Abstract:Landslides have become one of the dominant disasters all around the world. Reliable and efficient landslide mapping is playing a significant role in landslide studies. However, to the best of our knowledge, there is little research on detecting multiple landslides simultaneously from images to stimulate practical cases. In this work, we propose a regression model to detect landslides and investigate its applicability in practical cases. It synthesizes contextual, spectral and geometric features. Among the test images, F-measure of landslide detection has a range between 0.771 and 0.998, validating its robustness and high efficiency.
Keywords:Landslide detection  Probability regression  Random forest  Wenchuan earthquake
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