Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles
Abstract
:1. Introduction
1.1. Background Description
1.2. Related Works
1.2.1. Tourism Area Coverage Issues
1.2.2. Tourism Trajectory Planning Issues
1.2.3. Identified Gaps in the Literature and Contribution of This Paper
2. Problem Formulation
3. Main Results
3.1. Point Cloud Collection
3.2. The Coverage Path Planning of Ground Areas Using UAVs
3.2.1. Regional Decomposition
3.2.2. Coverage Path-Planning Strategy
3.3. The Three-Dimensional Tourism Trajectory Planning
3.3.1. Problem Definition
3.3.2. Three-Dimensional Trajectory-Planning Methods
- 1)
- Cost function of path length
- 2)
- Cost function of security
- 3)
- Climb altitude constraint
- 4)
- Smoothness cost function
- 5)
- Total cost function
- 1)
- Particle update equations
- 2)
- Position mapping
4. Experiment and Discussions
4.1. Search Coverage Flight Experiment and Discussions
4.1.1. Coverage Path-Planning Experiment 1
4.1.2. Coverage Path-Planning Experiment 2
4.2. Tourist Trajectory-Planning Simulation Experiment and Discussions
4.2.1. Selection of Trajectory Points
4.2.2. Selection of Obstacle Points
4.2.3. Simulation of Trajectory Planning
4.2.4. Refinement of Trajectory Planning
4.3. Limitations of the Study
5. Conclusions and Future Work
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
UAVs | Unmanned aerial vehicles |
GA | Genetic algorithm |
ACO | Ant colony algorithm |
PSO | Particle swarm optimization algorithm |
SPSO | Spherical vector-based PSO algorithm |
RNNs | Recurrent neural networks |
SAC | Soft actor–critic |
VRP | Vehicle routing problem |
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Test Number | UAV Count | Task Completion Time (min) | Path Value (km) | Setup Time for Each UAV (min) | Notes |
---|---|---|---|---|---|
1 | 1 | 27.87 | 129 | 4 | Task completion time for one UAV |
2 | 2 | 20.06 | 118.74 | 4 | Task completion time for two UAVs |
3 | 3 | 18.27 | 125.55 | 4 | Task completion time for three UAVs |
Test Number | UAV Count | Task Completion Time (min) | Path Value (km) | Setup Time for Each UAV (min) | Notes |
---|---|---|---|---|---|
1 | 1 Plane | 28.3567 | 185.4892 | 4 | Task completion time for one UAV |
2 | 2 Plane | 18.2345 | 175.7634 | 4 | Task completion time for one UAV |
3 | 3 Plane | 13.4567 | 172.08 | 4 | Task completion time for one UAV |
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© 2025 by the authors. Published by MDPI on behalf of the International Society for Photogrammetry and Remote Sensing. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Chen, Y.; Zhong, H.; Yu, J. Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles. ISPRS Int. J. Geo-Inf. 2025, 14, 145. https://doi.org/10.3390/ijgi14040145
Chen Y, Zhong H, Yu J. Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles. ISPRS International Journal of Geo-Information. 2025; 14(4):145. https://doi.org/10.3390/ijgi14040145
Chicago/Turabian StyleChen, Yu, Hui Zhong, and Jianglong Yu. 2025. "Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles" ISPRS International Journal of Geo-Information 14, no. 4: 145. https://doi.org/10.3390/ijgi14040145
APA StyleChen, Y., Zhong, H., & Yu, J. (2025). Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles. ISPRS International Journal of Geo-Information, 14(4), 145. https://doi.org/10.3390/ijgi14040145