Shaded Route Planning Using Active Segmentation and Identification of Satellite Images
<|reference_start|>Shaded Route Planning Using Active Segmentation and Identification of Satellite Images: 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.<|reference_end|>
@article{da2024shaded,
    title={Shaded Route Planning Using Active Segmentation and Identification of
  Satellite Images},
    author={Longchao Da, Rohan Chhibba, Rushabh Jaiswal, Ariane Middel, Hua Wei},
    journal={arXiv preprint arXiv:2407.13689},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.13689},
    primaryClass={cs.CY cs.AI cs.CV}
}