Shaded Route Planning Using Active Segmentation and Identification of Satellite Images

TL;DR

The paper tackles heat-related health risks by enabling shade-aware routing for pedestrians and cyclists. It introduces ShadeRouter, a pipeline that uses segmentation on high-resolution satellite imagery to identify shaded areas and constructs a multi-layer road graph that fuses shade information with distance data, enabling users to trade off exposure and travel length via $w_{joint} = \alpha V_{shade} + (1 - \alpha) V_{distance}$. A key contribution is the Shade Ratio Derivation, which computes $r(K) = \frac{L_{Shaded}}{L_{Acc}}$ to quantify shade along walkable/bikeable routes and integrates this into a universal shade layer $\mathcal{G}_{U}$ with type-specific layers from OSM. The authors provide an online demo based on a modified Dijkstra algorithm and release the code and datasets for replication, demonstrating real-time route planning that balances shade exposure against distance. The work enables health-conscious urban mobility planning and can be scaled to worldwide maps, with potential future enhancements including dynamic shading, wind information, and integration with shared mobility options, relevant for large-scale events like the 2024 Paris Olympics.

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.

Figures (3)

• Figure 1: The overview of the proposed pipeline for our shaded route planning method. The upper part shows the shaded ratio derivation process that takes the satellite image and OSM data as input, and calculates the shaded ratio for specific valid walkable or bikeable lanes. And the lower part shows the multi-layer road graph construction and route planning process, this reveals how ShadeRouter provides user preference shaded route planning from derived shadow information.
• Figure 2: The shaded ratio calculation, the yellow blocks show the shaded areas, and the red line shows valid routes from OSM data.
• Figure 3: The comparison between two itineraries by ShadeRouter in Paris. The shortest route in orange color is more exposed to heatwaves compared to the most shaded route, as shown in the snapshot of street views.