On Solving the Shortest Path of 3D Terrain Based on Remote Sensing Elevation Data and Ant Colony Optimization

Solving the shortest path of 3D terrain is widely requested. However, researchers have not been able to get a good solution due to the limitations of traditional technical means. Thanks to recent development and maturation of remote sensing technology, this paper presents a method of building 3D terrain model with remote sensing elevation data and finding the shortest path with Ant Colony Optimization (ACO). At the beginning, the paper analyzes the mainstream methods of solving the shortest path, and evaluates their advantages and disadvantages when applied to solving the shortest path in 3D space. In view of the excellent performance of the ACO, it is eventually adopted as the algorithm to solve the shortest path of 3D terrain. After introducing the principle and algorithm model of traditional 2D ACO, the paper improves the algorithm by re-designing the heuristic function, pheromone update strategy, and transfer rules, thereby applying the traditional algorithm to 3D space. After that, the author downloads and resamples the remote sensing elevation data of Shipping County, Yunnan Province, extracts the elevation data from the resampled data, and established a 3D mountain environment model. Based on the model, the author successfully conducts an experiment of solving the shortest path of 3D terrain with ACO.