How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine Debris
With coastal tourism depending on clean beaches and litter surveys remaining manual, sparse, and costly, this study coupled centimeter-resolution UAV imagery with a Grid R-CNN detector to automate debris mapping on five beaches of Wonsan Island, Korea. Thirty-one Phantom 4 flights (0.83 cm GSD) prod...
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MDPI AG
2025-06-01
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| Online Access: | https://www.mdpi.com/2073-445X/14/7/1349 |
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| author | Junho Ser Byungyun Yang |
| author_facet | Junho Ser Byungyun Yang |
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| description | With coastal tourism depending on clean beaches and litter surveys remaining manual, sparse, and costly, this study coupled centimeter-resolution UAV imagery with a Grid R-CNN detector to automate debris mapping on five beaches of Wonsan Island, Korea. Thirty-one Phantom 4 flights (0.83 cm GSD) produced 31,841 orthoimages, while 11 debris classes from the AI Hub dataset trained the model. The network reached 74.9% <i>mAP</i> and 78%/84.7% precision–recall while processing 2.87 images s<sup>−1</sup> on a single RTX 3060 Ti, enabling a 6 km shoreline to be surveyed in under one hour. Georeferenced detections aggregated to 25 m grids showed that 57% of high-density cells lay within 100 m of the beach entrances or landward edges, and 86% within 200 m. These micro-patterns, which are difficult to detect in meter-scale imagery, suggest that entrance-focused cleanup strategies could reduce annual maintenance costs by approximately one-fifth. This highlights the potential of centimeter-scale GeoAI in supporting sustainable beach management. |
| format | Article |
| id | doaj-art-19cb24e6d94a47d895e8f8e7b00628dd |
| institution | DOAJ |
| issn | 2073-445X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-19cb24e6d94a47d895e8f8e7b00628dd2025-08-20T02:45:56ZengMDPI AGLand2073-445X2025-06-01147134910.3390/land14071349How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine DebrisJunho Ser0Byungyun Yang1Geospatial Science Lab, Dongguk University—Seoul Campus, 30, Pildong-ro 1-gil, Jung-gu, Seoul 04620, Republic of KoreaDepartment of Geography Education, Dongguk University—Seoul Campus, 30, Pildong-ro 1-gil, Jung-gu, Seoul 04620, Republic of KoreaWith coastal tourism depending on clean beaches and litter surveys remaining manual, sparse, and costly, this study coupled centimeter-resolution UAV imagery with a Grid R-CNN detector to automate debris mapping on five beaches of Wonsan Island, Korea. Thirty-one Phantom 4 flights (0.83 cm GSD) produced 31,841 orthoimages, while 11 debris classes from the AI Hub dataset trained the model. The network reached 74.9% <i>mAP</i> and 78%/84.7% precision–recall while processing 2.87 images s<sup>−1</sup> on a single RTX 3060 Ti, enabling a 6 km shoreline to be surveyed in under one hour. Georeferenced detections aggregated to 25 m grids showed that 57% of high-density cells lay within 100 m of the beach entrances or landward edges, and 86% within 200 m. These micro-patterns, which are difficult to detect in meter-scale imagery, suggest that entrance-focused cleanup strategies could reduce annual maintenance costs by approximately one-fifth. This highlights the potential of centimeter-scale GeoAI in supporting sustainable beach management.https://www.mdpi.com/2073-445X/14/7/1349GeoAImarine debrisUAV imageryobject detectioncoastal tourismbeach management |
| spellingShingle | Junho Ser Byungyun Yang How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine Debris Land GeoAI marine debris UAV imagery object detection coastal tourism beach management |
| title | How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine Debris |
| title_full | How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine Debris |
| title_fullStr | How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine Debris |
| title_full_unstemmed | How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine Debris |
| title_short | How GeoAI Improves Tourist Beach Environments: Micro-Scale UAV Detection and Spatial Analysis of Marine Debris |
| title_sort | how geoai improves tourist beach environments micro scale uav detection and spatial analysis of marine debris |
| topic | GeoAI marine debris UAV imagery object detection coastal tourism beach management |
| url | https://www.mdpi.com/2073-445X/14/7/1349 |
| work_keys_str_mv | AT junhoser howgeoaiimprovestouristbeachenvironmentsmicroscaleuavdetectionandspatialanalysisofmarinedebris AT byungyunyang howgeoaiimprovestouristbeachenvironmentsmicroscaleuavdetectionandspatialanalysisofmarinedebris |