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High-resolution Image based Landslides Dataset in Loess Plateau

HU Sheng1,2,3QIU Haijun1,2,3WANG Ninglian1,2,3CUI Yifei4CAO Mingming1
1 Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity,Northwest University,Xi'an 710127,China2 Institute of Earth Surface System and Hazards,Northwest University,Xi'an 710127,China3 College of Urban and Environmental Sciences,Northwest University,Xi'an 710127,China4 State Key Laboratory of Hydroscience and Engineering,Tsinghua University,Beijing 100084,China


Published:Jul. 2020

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Key Words:

Loess Plateau,landslides,Quaternary Sciences,Geomorphology


From March 2017 to November 2018, the authors spent more than 20 months on the field UAV survey of landslides on six typical routes in Loess Plateau, covering a total distance of more than 7,000 km: (1) Xi’an-Baoji-Tianshui-Qin’an-Dingxi-Lanzhou-Heifangtai-Xining; (2) Xi’an-Xianyang-Pingliang-Huining-Dingxi; (3) Xi’an-Bailu Tableland-Lantian-Jingyang; (4) Xi’an-Tongchuan-Yan’an-Zhidan-Yulin-Erdos; (5) Xi’an-Weinan-Heyang; and (6) Xi’an-Weinan-Sanmenxia-Yuncheng-Lishi-Linfen. 108 loess landslide high-resolution images and terrain data were collected. At the same time, the interpretation of 199 landslides was completed by using Google satellite images and Japanese AW3D 5m-DSM terrain data. Finally, ArcGIS 10.5 and Global Mapper 17.0 were used to extract geometric and topographic characteristic parameters and other information of 307 loess landslides, and the data cataloging work was completed to obtain the high-resolution image based landslides dataset in Loess Plateau. The dataset includes: (1) 307 landslides’ code, Coordinates, Length, Width, L/W ratio, Perimeter, Area, Elevation difference, Slope, Azimuth, Landform and Source; 2) photos of typical landslides. The dataset is archived in.shp, .jpg and .docx data formats, it consists of 17 data files with data size of 38.9 MB (compressed to one single file with data size of 38.5MB).The research articles based on the dataset have been published in: (1) Doctoral Dissertation Database of CNKI, Title “Spatial pattern of landslide in Loess Plateau and its influence on geomorphologic evolution”, 2019; (2) Quaternary Sciences, 2018, 38(2); (3) Landslides, 2018, 15(3); (4) Landslides, 2019, 16(3); (5) Geomorphology, 2020, 359: 107167.

Foundation Item:

Chinese Academy of Sciences (131551KYSB20160002); National Natural Science Foundation of China (41771539)

Data Citation:

HU Sheng, QIU Haijun, WANG Ninglian, CUI Yifei, CAO Mingming. High-resolution Image based Landslides Dataset in Loess Plateau[J/DB/OL]. Digital Journal of Global Change Data Repository, 2020.

Data Product:

ID Data Name Data Size Operation
1 LandslidesLoessPlateau.rar 39486.75KB