Shaded Route Planning Using Active Segmentation and Identification of Satellite Images
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866913435498840064 |
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| author | Da, Longchao Chhibba, Rohan Jaiswal, Rushabh Middel, Ariane Wei, Hua |
| author_facet | Da, Longchao Chhibba, Rohan Jaiswal, Rushabh Middel, Ariane Wei, Hua |
| contents | Heatwaves pose significant health risks, particularly due to prolonged exposure to high summer temperatures. Vulnerable groups, especially pedestrians and cyclists on sun-exposed sidewalks, motivate the development of a route planning method that incorporates somatosensory temperature effects through shade ratio consideration. This paper is the first to introduce a pipeline that utilizes segmentation foundation models to extract shaded areas from high-resolution satellite images. These areas are then integrated into a multi-layered road map, enabling users to customize routes based on a balance between distance and shade exposure, thereby enhancing comfort and health during outdoor activities. Specifically, we construct a graph-based representation of the road map, where links indicate connectivity and are updated with shade ratio data for dynamic route planning. This system is already implemented online, with a video demonstration, and will be specifically adapted to assist travelers during the 2024 Olympic Games in Paris. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_13689 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Shaded Route Planning Using Active Segmentation and Identification of Satellite Images Da, Longchao Chhibba, Rohan Jaiswal, Rushabh Middel, Ariane Wei, Hua Computers and Society Artificial Intelligence Computer Vision and Pattern Recognition 68T45, 68U35 I.2.10; I.4.8 Heatwaves pose significant health risks, particularly due to prolonged exposure to high summer temperatures. Vulnerable groups, especially pedestrians and cyclists on sun-exposed sidewalks, motivate the development of a route planning method that incorporates somatosensory temperature effects through shade ratio consideration. This paper is the first to introduce a pipeline that utilizes segmentation foundation models to extract shaded areas from high-resolution satellite images. These areas are then integrated into a multi-layered road map, enabling users to customize routes based on a balance between distance and shade exposure, thereby enhancing comfort and health during outdoor activities. Specifically, we construct a graph-based representation of the road map, where links indicate connectivity and are updated with shade ratio data for dynamic route planning. This system is already implemented online, with a video demonstration, and will be specifically adapted to assist travelers during the 2024 Olympic Games in Paris. |
| title | Shaded Route Planning Using Active Segmentation and Identification of Satellite Images |
| topic | Computers and Society Artificial Intelligence Computer Vision and Pattern Recognition 68T45, 68U35 I.2.10; I.4.8 |
| url | https://arxiv.org/abs/2407.13689 |