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Estimation of Landslides and Road Capacity after August 8, 2017, MS7.0 Jiuzhaigou Earthquake Using High-Resolution Remote Sensing Images
On 8 August 2017, Jiuzhaigou earthquake, magnitude 7.0, hit northern Sichuan, China. As the earthquake-stricken area is located in the mountainous region with forest and low residential density, the main damage is to vegetation and roads by earthquake-triggered landslides. In this study, the core area of Jiuzhaigou natural reserve, one of the highest seismic intensity zones, is selected. The landslides are extracted by examining vegetation changes from the preearthquake and postearthquake images using the Normalized Difference Vegetation Index (NDVI) and are verified by slope. As most road damage in the mountainous region could be attributed to the landslides nearby, the impacts of landslide on road are studied based on spatial analysis and are used to infer occluded road damage. Then, a knowledge-based method for postearthquake road detection and road capacity assessment from preearthquake road data and postearthquake high-resolution remote sensing imagery is proposed, as well as the quantitative road capacity assessment indicators to classify the road grades. This method is evaluated using the Beijing-2 (BJ-2) satellite images over the study area acquired on 28 April and 9 August. Compared with visual interpretation results, the extraction accuracy reached 90% for landslides and 85% for postearthquake roads, indicating that the approaches are effective and promising for quick response to devastating earthquake in similar circumstances.
Estimation of Landslides and Road Capacity after August 8, 2017, MS7.0 Jiuzhaigou Earthquake Using High-Resolution Remote Sensing Images
On 8 August 2017, Jiuzhaigou earthquake, magnitude 7.0, hit northern Sichuan, China. As the earthquake-stricken area is located in the mountainous region with forest and low residential density, the main damage is to vegetation and roads by earthquake-triggered landslides. In this study, the core area of Jiuzhaigou natural reserve, one of the highest seismic intensity zones, is selected. The landslides are extracted by examining vegetation changes from the preearthquake and postearthquake images using the Normalized Difference Vegetation Index (NDVI) and are verified by slope. As most road damage in the mountainous region could be attributed to the landslides nearby, the impacts of landslide on road are studied based on spatial analysis and are used to infer occluded road damage. Then, a knowledge-based method for postearthquake road detection and road capacity assessment from preearthquake road data and postearthquake high-resolution remote sensing imagery is proposed, as well as the quantitative road capacity assessment indicators to classify the road grades. This method is evaluated using the Beijing-2 (BJ-2) satellite images over the study area acquired on 28 April and 9 August. Compared with visual interpretation results, the extraction accuracy reached 90% for landslides and 85% for postearthquake roads, indicating that the approaches are effective and promising for quick response to devastating earthquake in similar circumstances.
Estimation of Landslides and Road Capacity after August 8, 2017, MS7.0 Jiuzhaigou Earthquake Using High-Resolution Remote Sensing Images
Xiao Fu (author) / Qing Zhu (author) / Chao Liu (author) / Naiwen Li (author) / Wenhua Zhuang (author) / Zhengli Yang (author) / Heng Lu (author) / Min Tang (author)
2020
Article (Journal)
Electronic Resource
Unknown
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