Shaded Route Planning Using Active Segmentation and Identification of Satellite Images

Longchao Da, Rohan Chhibba, Rushabh Jaiswal, Ariane Middel, Hua Wei
7/18/2024
cs.CYcs.AIcs.CV

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Abstract

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.

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Cite this paper

@article{da2024shaded,
  title  = {Shaded Route Planning Using Active Segmentation and Identification of Satellite Images},
  author = {Longchao Da and Rohan Chhibba and Rushabh Jaiswal and Ariane Middel and Hua Wei},
  year   = {2024},
  eprint = {2407.13689},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.13689v1}
}

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