{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T05:38:28Z","timestamp":1780465108636,"version":"3.54.1"},"reference-count":34,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:00:00Z","timestamp":1743033600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Phased achievements from construction of environmental design major in the Ministry of Education\u2019s National First-Class Undergraduate Major Construction Program","award":["3320109620210144"],"award-info":[{"award-number":["3320109620210144"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>In this study, we analyzed regional spatial features and optimized tourism routes based on point cloud data provided by unmanned aerial vehicles (UAVs) with the goal of developing the Xiaosongyuan Red Tourism Scenic Area in Kunming, Yunnan Province, China. We first proposed a novel method for UAV point cloud data coverage based on an irregular regional segmentation technique along with an optimized search path designed to minimize travel time within the specified area. Three DJI Phantom drones were employed to collect data over the designated region, and an improved progressive triangular irregular network densification filtering algorithm was used to extract ground points from the UAV-acquired point cloud data. DJI Terra software was used for image stitching to generate a comprehensive map of spatial features in the target area. Using this three-dimensional map of spatial features, we explored tourist routes in complex environments and applied an improved particle swarm optimization algorithm to identify optimal tourist routes characterized by safety, smoothness, and feasibility. The findings provide valuable technical support for enhancing tourism planning and management in scenic areas while maintaining a balance with conservation efforts.<\/jats:p>","DOI":"10.3390\/ijgi14040145","type":"journal-article","created":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T12:41:02Z","timestamp":1743079262000},"page":"145","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles"],"prefix":"10.3390","volume":"14","author":[{"given":"Yu","family":"Chen","sequence":"first","affiliation":[{"name":"Faculty of Art and Communication, Kunming University of Science and Technology, Kunming 650500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Zhong","sequence":"additional","affiliation":[{"name":"Faculty of Art and Communication, Kunming University of Science and Technology, Kunming 650500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianglong","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/MGRS.2021.3122248","article-title":"Unmanned Aerial Vehicle-Based Photogrammetric 3D Mapping: A survey of techniques, applications, and challenges","volume":"10","author":"Jiang","year":"2021","journal-title":"IEEE Geosci. 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