Geographic information spatial feature extraction based on drone aerial surveying and mapping technology

Yonglin Lai; Yang Li

doi:10.1117/12.3029424

16 May 2024 Geographic information spatial feature extraction based on drone aerial surveying and mapping technology

Yonglin Lai, Yang Li

Proceedings Volume 13166, International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024); 131660B (2024) https://doi.org/10.1117/12.3029424
Event: International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024), 2024, Changchun, China

Abstract

In response to the problem that traditional surveying and mapping methods are difficult to adapt to complex terrain environments and have low accuracy in extracting geographic information spatial features, a research on geographic information spatial feature extraction based on drone aerial surveying and mapping technology is proposed. Based on unmanned aerial vehicle (UAV) aerial surveying and mapping technology, geographic information spatial images are obtained, and offset parameters and distortion coefficients are introduced to achieve the acquisition and correction of geographic information spatial images; Cluster the geographic information spatial features of similar targets into a set of set data, and convert their coordinates using world coordinates and pixel coordinates as references. Using orthogonal vectors between geographic information spaces to describe geographic information spatial features and achieve geographic information spatial feature extraction. The experimental results show that the highest elevation accuracy of the geographic information spatial feature extraction method in this article is 0.5m, with an average data coverage of 97.5% and an average data consistency of 97.5%.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yonglin Lai and Yang Li "Geographic information spatial feature extraction based on drone aerial surveying and mapping technology", Proc. SPIE 13166, International Conference on Remote Sensing Technology and Survey Mapping (RSTSM 2024), 131660B (16 May 2024); https://doi.org/10.1117/12.3029424

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