Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data

被引:38
|
作者
Fan, Jian-rong [1 ]
Zhang, Xi-yu [1 ,2 ]
Su, Feng-huan [1 ]
Ge, Yong-gang [1 ]
Tarolli, Paolo [3 ]
Yang, Zheng-yin [4 ]
Zeng, Chao [5 ]
Zeng, Zhen [5 ]
机构
[1] Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Earth Surface Proc, Chengdu 610041, Sichuan, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Univ Padua, Dept Land Environm Agr & Forestry, Agripolis, Viale Univ 16, I-35020 Legnaro, PD, Italy
[4] Sichuan Remote Sensing Informat Surveying & Mappi, Chengdu 610100, Sichuan, Peoples R China
[5] Sichuan Geomat Ctr, Sichuan Engn Res Ctr Emergency Mapping & Disaster, Chengdu 610041, Sichuan, Peoples R China
关键词
Xinmo Landslide; Geological disaster; Remote Sensing; Unmanned aerial vehicle (UAV); Digital elevation model (DEM); Satellite data; 2008 WENCHUAN EARTHQUAKE; SICHUAN PROVINCE; TOPOGRAPHY; DEFORMATION; AREAS; UAV;
D O I
10.1007/s11629-017-4633-3
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
At 5:39 am on June 24, 2017, a landslide occurred in the village of Xinmo in Maoxian County, Aba Tibet and Qiang Autonomous Prefecture (Sichuan Province, Southwest China). On June 25, aerial images were acquired from an unmanned aerial vehicle (UAV), and a digital elevation model (DEM) was processed. Landslide geometrical features were then analyzed. These are the front and rear edge elevation, accumulation area and horizontal sliding distance. Then, the volume and the spatial distribution of the thickness of the deposit were calculated from the difference between the DEM available before the landslide, and the UAV-derived DEM collected after the landslide. Also, the disaster was assessed using high-resolution satellite images acquired before the landslide. These include QuickBird, Pleiades-1 and GF-2 images with spatial resolutions of 0.65 m, 0.70 m, and 0.80 m, respectively, and the aerial images acquired from the UAV after the landslide with a spatial resolution of 0.1 m. According to the analysis, the area of the landslide was 1.62 km(2), and the volume of the landslide was 7.70 +/- 1.46 million m(3). The average thickness of the landslide accumulation was approximately 8 m. The landslide destroyed a total of 103 buildings. The area of destroyed farmlands was 2.53 ha, and the orchard area was reduced by 28.67 ha. A 2-km section of Songpinggou River was blocked and a 2.1-km section of township road No. 104 was buried. Constrained by the terrain conditions, densely populated and more economically developed areas in the upper reaches of the Minjiang River basin are mainly located in the bottom of the valleys. This is a dangerous area regarding landslide, debris flow and flash flood events. Therefore, in mountainous, high-risk disaster areas, it is important to carefully select residential sites to avoid a large number of casualties.
引用
收藏
页码:1677 / 1688
页数:12
相关论文
共 50 条
  • [1] Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data
    FAN Jian-rong
    ZHANG Xi-yu
    SU Feng-huan
    GE Yong-gang
    Paolo TAROLLI
    YANG Zheng-yin
    ZENG Chao
    ZENG Zhen
    JournalofMountainScience, 2017, 14 (09) : 1677 - 1688
  • [2] Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data
    Jian-rong Fan
    Xi-yu Zhang
    Feng-huan Su
    Yong-gang Ge
    Paolo Tarolli
    Zheng-yin Yang
    Chao Zeng
    Zhen Zeng
    Journal of Mountain Science, 2017, 14 : 1677 - 1688
  • [3] Erratum to: Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data
    Jian-rong Fan
    Xi-yu Zhang
    Feng-huan Su
    Yong-gang Ge
    Paolo Tarolli
    Zheng-yin Yang
    Chao Zeng
    Zhen Zeng
    Journal of Mountain Science, 2017, 14 : 2136 - 2136
  • [4] Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data (vol 14,pg 1677, 2017)
    Fan Jian-rong
    Zhang Xi-yu, .
    Su Feng-huan
    Ge Yong-gang
    Tarolli, Paolo
    Yang Zheng-yin
    Zeng Chao
    Zeng Zhen
    JOURNAL OF MOUNTAIN SCIENCE, 2017, 14 (10) : 2136 - 2136
  • [5] Uncertainty Analysis of Flood Disaster Assessment Using Remote Sensing Data
    Du, Cong
    Yan, Fuli
    Liu, Jing
    2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 1071 - 1073
  • [6] The study on disaster assessment of snow in pastoral areas based on remote sensing data
    National Disaster Reduction Center of China, No 6 Guangbaidong Road, Chaoyang District, Beijing, 100124, China
    不详
    不详
    Proc SPIE Int Soc Opt Eng,
  • [7] The study on disaster assessment of snow in pastoral areas based on remote sensing data
    Nie, Juan
    Cheng, Yaoying
    Li, Wenbo
    Tang, Tong
    Fan, Yida
    MIPPR 2011: MULTISPECTRAL IMAGE ACQUISITION, PROCESSING, AND ANALYSIS, 2011, 8002
  • [8] Landslide Recognition from Multi-Feature Remote Sensing Data Based on Improved Transformers
    Huang, Renxiang
    Chen, Tao
    REMOTE SENSING, 2023, 15 (13)
  • [9] Remote Sensing Monitoring of Hail Disaster Based on Spectral Feature
    Li, Chengfan
    Yin, Jingyuan
    Zhao, Junjuan
    Shan, Xinjian
    Liu, Lan
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2011, 14 (03): : 699 - 704
  • [10] Reconstruction and Visualization of Landslide Events Based on Pre- and Post-Disaster Remote Sensing Data
    Luo, Zhaolin
    Yang, Jiali
    Huang, Bolin
    Chen, Wufen
    Gao, Yishan
    Meng, Qingkui
    WATER, 2023, 15 (11)