IMHE OpenIR  > Journal of Mountain Science  > Journal of Mountain Science-2017  > Vol14 No.9
Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data
Fan, Jian-rong1; Zhang, Xi-yu1,2; Su, Feng-huan1; Ge, Yong-gang1; Tarolli, Paolo3; Yang, Zheng-yin4; Zeng, Chao5; Zeng, Zhen5
2017
Source PublicationJOURNAL OF MOUNTAIN SCIENCE
ISSN1672-6316
EISSN1993-0321
Volume14Issue:9Pages:1677-1688
SubtypeArticle
AbstractAt 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.
KeywordXinmo Landslide Geological Disaster Remote Sensing Unmanned Aerial Vehicle (Uav) Digital Elevation Model (Dem) Satellite Data
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.1007/s11629-017-4633-3
WOS Subject ExtendedEnvironmental Sciences & Ecology
Indexed BySCI
WOS KeywordHIGH-RESOLUTION TOPOGRAPHY ; 2008 WENCHUAN EARTHQUAKE ; SURFACE PROCESSES ; SICHUAN PROVINCE ; CHINA ; PHOTOGRAMMETRY ; DEFORMATION ; EROSION ; AREAS ; JAPAN
Language英语
Quartile4区
TOP
WOS SubjectEnvironmental Sciences
WOS IDWOS:000409490000001
Funding OrganizationNational Key Technologies R&D Program of China(2017YFC0505104) ; Key Laboratory of Digital Mapping and Land Information Application of National Administration of Surveying, Mapping and Geoinformation of China(DM2016SC09)
PublisherSCIENCE PRESS
Citation statistics
Cited Times:22[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/19066
CollectionJournal of Mountain Science_Journal of Mountain Science-2017_Vol14 No.9
山地灾害与地表过程重点实验室
数字山地与遥感应用中心
Corresponding AuthorSu, Feng-huan
Affiliation1.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
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Corresponding Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
Fan, Jian-rong,Zhang, Xi-yu,Su, Feng-huan,et al. Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data[J]. JOURNAL OF MOUNTAIN SCIENCE,2017,14(9):1677-1688.
APA Fan, Jian-rong.,Zhang, Xi-yu.,Su, Feng-huan.,Ge, Yong-gang.,Tarolli, Paolo.,...&Zeng, Zhen.(2017).Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data.JOURNAL OF MOUNTAIN SCIENCE,14(9),1677-1688.
MLA Fan, Jian-rong,et al."Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data".JOURNAL OF MOUNTAIN SCIENCE 14.9(2017):1677-1688.
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