RAPID EXTRACTION OF LANDSLIDE AND SPATIAL DISTRIBUTION ANALYSIS AFTER JIUZHAIGOU Ms7.0 EARTHQUAKE BASED ON UAV IMAGES
Jiuzhaigou earthquake led to the collapse of the mountains and formed lots of landslides in Jiuzhaigou scenic spot and surrounding roads which caused road blockage and serious ecological damage. Due to the urgency of the rescue, the authors carried unmanned aerial vehicle (UAV) and entered the disas...
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Veröffentlicht in: | International archives of the photogrammetry, remote sensing and spatial information sciences. remote sensing and spatial information sciences., 2018-04, Vol.XLII-3, p.685-690 |
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Sprache: | eng |
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Zusammenfassung: | Jiuzhaigou earthquake led to the collapse of the mountains and formed lots of landslides in Jiuzhaigou scenic spot and surrounding roads which caused road blockage and serious ecological damage. Due to the urgency of the rescue, the authors carried unmanned aerial vehicle (UAV) and entered the disaster area as early as August 9 to obtain the aerial images near the epicenter. On the basis of summarizing the earthquake landslides characteristics in aerial images, by using the object-oriented analysis method, landslides image objects were obtained by multi-scale segmentation, and the feature rule set of each level was automatically built by SEaTH (Separability and Thresholds) algorithm to realize the rapid landslide extraction. Compared with visual interpretation, object-oriented automatic landslides extraction method achieved an accuracy of 94.3 %. The spatial distribution of the earthquake landslide had a significant positive correlation with slope and relief and had a negative correlation with the roughness, but no obvious correlation with the aspect. The relationship between the landslide and the aspect was not found and the probable reason may be that the distance between the study area and the seismogenic fault was too far away. This work provided technical support for the earthquake field emergency, earthquake landslide prediction and disaster loss assessment. |
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ISSN: | 2194-9034 1682-1750 2194-9034 |
DOI: | 10.5194/isprs-archives-XLII-3-685-2018 |