Fusion of UAV image and LiDAR point cloud to study the detection technology of mountain surface cover landscape characteristics

doi:10.13474/j.cnki.11-2246.2022.0020

Abstract

Abstract: Airborne LiDAR data can accurately provide three-dimensional spatial location information of objects, and UAV high-resolution image has rich color information and texture information. By integrating the advantages of two kinds of data expression, data integration and fusion are carried out. Aiming at the matrix landscape of the most widely distributed vegetation cover type in mountainous areas, this paper proposes to construct visible vegetation index (VDVI) and then carry out the research on the typical vegetation feature extraction of the fusion spectral information point cloud data based on this technology. In order to verify the accuracy of the method, three data sources are constructed and the mountain is carried out in turn. The experiment of vegetation extraction in the area. The qualitative and quantitative analysis of the experimental results shows that the vegetation coverage rate of the fusion spectral point cloud data is 56.8%, which is closer to the reference value of 58.2% than the other two data types. The credibility is relatively high, the effect is better, the vegetation patch contour is clearer, and it is more suitable for the target object vegetation feature extraction, so that the advantages of the fusion image information point cloud data classification can be reflected. The feasibility of this classification method for mountain vegetation feature extraction is discussed.

Key words: UAV image, LiDAR data, data fusion, visible light vegetation index, vegetation coverage rate

CLC Number:

P237

GAO Sha, YUAN Xiping, GAN Shu, YANG Minglong, YUAN Xinyue, LUO Weidong. Fusion of UAV image and LiDAR point cloud to study the detection technology of mountain surface cover landscape characteristics[J]. Bulletin of Surveying and Mapping, 2022, 0(1): 110-115.

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