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In Situ Dataset of Loess Sinkholes using UAS and LiDAR Technology in Huining County, China (2021)

HU Sheng1,2JIANG Zongda3WANG Ninglian*1,2ZHANG Fanyu*4CHEN Yixian1,2WU Songbai1,2WANG Lin3LI Sisi3
1 Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity,Northwest University,Xi’an 710127,China2 College of Urban and Environmental Sciences,Northwest University,Xi’an 710127,China3 School of Information Science and Technology,Northwest University,Xi’an 710127,China4 College of Civil Engineering and Mechanics,Lanzhou University,Lanzhou 730000,China


Published:May 2024

Visitors:600       Data Files Downloaded:11      
Data Downloaded:6696.37 MB      Citations:

Key Words:

Loess sinkholes,morphology,soil erosion,UAS survey,LiDAR


In 2021, the authors conducted a refined investigation of the loess sinkholes on the river terraces of Laozi Gully in Huining County, Gansu Province, using an Unmanned Aerial System (UAS) and a Hand-Held Laser Scanner (HLS). Digital orthophoto map of study area and 3D laser point cloud data of each sinkhole were acquired. In terms of post-processing of the data, the authors completed the interpretation of the sinkholes and the construction of the database in ArcGIS 10.5. They also carried out point cloud data processing, modeling, and volume calculation in CloudCompare, Geomagic Wrap 2021, and Python. The dataset includes: (1) basic geospatial data, which encompasses boundary of study area, distribution of sinkholes (polygons and points), UAS DOM and hillshade; (2) a morphological feature parameter table and soil erosion calculation attributes for 142 sinkholes, including 17 parameters such as ID, major axis, minor axis, elongation ratio, eccentricity, perimeter, area, volume, and soil loss, etc.; (3) field survey photos and videos; (4) refined LiDAR point cloud data for each sinkhole; (5) modeling data for typical sinkholes in CloudComapre; (6) a Python-based custom-developed volume calculation slicing scheme for each sinkhole, with results stored in the attribute table; (7) point cloud encapsulation model of each sinkhole constructed using Geomagic Wrap 2021, with volume calculation results stored in the attribute table. The dataset is archived in .JPG, .mp4, .bin, .txt, .wrp, .pdf, .xlsx, and .shp formats, and consists of 712 data files with data size of 1.59 GB (Compressed into 2 files with 1.16 GB). In the dataset, the point cloud data in .bin and .txt formats can be opened with the open-source software CloudCompare, while .wrp format model data can be utilized with Geomagic Wrap 2021.

Foundation Item:

National Natural Science Foundation of China (42371009, 42001006); Undergraduate Talent Training Construction Project of Northwest University (2023-38); Northwestern University Graduate Research and Innovation Project (2024-212)

Data Citation:

HU Sheng, JIANG Zongda, WANG Ninglian*, ZHANG Fanyu*, CHEN Yixian, WU Songbai, WANG Lin, LI Sisi. In Situ Dataset of Loess Sinkholes using UAS and LiDAR Technology in Huining County, China (2021)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024.


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Data Product:

ID Data Name Data Size Operation
1 SinkholesHuining2021_1.rar 637065.88KB
2 SinkholesHuining2021_2.rar 586851.36KB