Automated Station Planning for Terrestrial Laser Scanning in Complex Forest Environments

Abstract. Terrestrial laser scanning technology can efficiently acquire highTerrestrial laser scanning technology can efficiently acquire high high-precision three three-dimensional spatial information in complex forest environments, making it an important technical means for detailed analysis of forest structure and resource monitoring. How ever, traditional terrestrial laser scanners planning methods are prone to coverage gaps and data redundancy due to factors such as tree obstructions, terrain undulations, and canopy overlap, making it difficult to simultaneously balance observation comple teness and scanner station deployment cost. To address this, this paper proposes a n intelligent survey station planning for terrestrial laser scanners in complex forest environments . The method first uses UAV LiDAR data to build a prior forest model , which is then used to quantitatively evaluate forest visibility features by calculating the cumulative visible central angle through visibility analysis analysis. Finally, an integer linear programming model is further introduced to achieve global optimization of the st ation set based on an initial feasible coverage solution obtained using a greedy algorithminitial feasible coverage solution obtained using a greedy algorithm algorithm. To test the performance of the proposed method, this paper applies the proposed method to the forest plot located in Lushan city, Jiangxi province, China. Experimen tal results indicate that the proposed method achieves an overall coverage rate of 94.55% with only seven stations, reducing the number of stations by approximately 30% and 22% compared with the greedy algorithm and genetic algorithm, respectively. The res ults demonstrate the effectiveness and superiority of this method for station planning in complex forest areas and provide efficient and precise technical support for forest structure monitoring and spatial information acquisition.