Performance of Affordable 2D Cave Scanning Technique from LiDAR for Constructing 3D Cave Models

This research presents a new approach to the cave 3D model construction by a combination of a cave two-dimensional profile scanning using a low-cost modified 2D LiDAR, and data processing via a computer-aided design (CAD) software. The proposed technique has been tested to create 3D models of three...

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Bibliographic Details
Published inAdvanced LiDAR Vol. 4; no. 1; pp. 1 - 8
Main Authors Promneewat, Khomchan, Taksavasu, Tadsuda
Format Journal Article
LanguageEnglish
Published Atlas Akademi 31.03.2024
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Summary:This research presents a new approach to the cave 3D model construction by a combination of a cave two-dimensional profile scanning using a low-cost modified 2D LiDAR, and data processing via a computer-aided design (CAD) software. The proposed technique has been tested to create 3D models of three Permian limestone caves in northern Thailand, namely Chiang-Dao, Muang-On, and San-Han. The entire method takes 27-30 hours to achieve, covering approximately 614.59 meters of the total survey distance and generating an overall cave volume of 41,310.0 m³. The resulting 3D models ultimately resemble the shape, orientation, and dimension of the caves, exhibiting burrow-like, irregular-shaped, and some deformation-induced features. The proposed LiDAR scanning method appears to be relatively cheap and fast compared to other scanning methods as it has the working speed of 63.5 meters per hour costing less than $200 USD. These findings distinctly indicate that the developed data processing of cave scanning profiles using 2D LiDAR is affordable and meets the need for cave 3D modeling. However, there are minor limitations, including missing data among the scanned profiles and overlaps of cave features formed in the sidewalls. The cave models produced here can be used as reference sources for geoscientific research, geotourism, georesource management, and other research activities in caves. Further hardware and software development is strongly recommended to improve the existing methods.
ISSN:2791-8572