Methods and Applications of Section Extraction Based on Airborne LiDAR Point Cloud Data
Traditional cross-section surveying is characterized by high labor intensity,low efficiency,and low automation.To address the significant errors encountered in conventional commercial software when extracting cross-sections in gullies and embankments,this paper proposes the Point Cloud Forward Search Method and Point Cloud Shrinkage Iteration Method for cross-section extraction.Using point cloud data acquired by airborne LiDAR as the raw data,the proposed algorithms are applied to obtain cross-section data.In order to verify the accuracy of the algorithms,GPS-RTK manual mapping method is conducted at the same locations to obtain cross-section data,which serves as a reference for validating the algorithm results.Furthermore,the proposed methods are compared with the Vertical Offset Method for point cloud extraction.The results indicate that the cross-section data extracted by the proposed methods closely match the GPS-RTK surveyed data.These methods can provide accurate spatial data support for terrain analysis,engineering design,natural resource management,land use planning,and disaster risk assessment,offering reliable geographic information for decision-makers and planners.
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