Abstract
Automatic detection of landslides using remote sensing images has been demonstrated to be an effective method in landslide inventory mapping. However, areas recognized as landslides using traditional methods may connect with each other and form a massive landslide, which is not conducive for accurate statistics on the number of individual landslides. Thus, this paper explored an object-oriented individual landslide separation method to solve this issue. The landslide areas were obtained by applying an object-oriented detection method on a SPOT-5 2.5 m multispectral image and the field investigation. A sequence of processes including the multi-scale image segmentation, spectral characteristics difference analysis, morphometric properties for landslides selection was applied. Objects detected as landslides were subsequently separated into individual landslides. Comparison of model results indicates that the proposed method can divide the landslide areas into individuals better than just merging them directly. It is also relatively quick to use this method to separate individual landslides than to use visual interpretation. Therefore, the object-oriented individual landslides separation method proposed in this paper could be a good solution for rapid risk assessment of landslide disasters.
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Acknowledgements
This research was primarily supported by the National Key Technology R & D Program of the Twelfth Five-Year of China (No. 2012BAK10B03), the High-Resolution Special Scientific Research Project from the National Disaster Reduction Center of China, Ministry of Civil Affairs (No. 03-Y30B06-9001-13/15).
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Lin, Q., Zou, Z., Lin, L., Wang, Y. (2017).
Combining Spectral and Morphometric Properties of Landslides for Separating Individual Landslides Based on Object-Oriented Method.
In: Mikos, M., Tiwari, B., Yin, Y., Sassa, K. (eds) Advancing Culture of Living with Landslides. WLF 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-53498-5_8
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DOI: https://doi.org/10.1007/978-3-319-53498-5_8
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