arXiv:2605.20510v1 Announce Type: cross Abstract: Urban heat exposure is becoming an increasingly critical challenge due to the intensifying urban heat island effect. Fine-grained shade patterns, especially those induced by urban buildings, strongly influence pedestrians' thermal exposure and outdoor activity planning. However, accurately modeling and analyzing urban shade at scale remains difficult because of the lack of large-scale datasets and systematic evaluation frameworks. To address this challenge, we present ShadeBench, a comprehensive dataset and benchmark for urban shade understandi
The increasing urgency of urban climate challenges, particularly the urban heat island effect, is driving innovation in climate resilience and urban planning using AI.
This benchmark dataset provides a critical foundation for developing AI models that can accurately simulate urban shade, which is vital for sustainable urban design and public health.
The availability of a comprehensive dataset like ShadeBench will accelerate research and practical applications for mitigating urban heat and improving outdoor thermal comfort in cities.
- · Urban planners
- · Smart city initiatives
- · AI/ML researchers in remote sensing
- · Sustainable development companies
- · Cities unprepared for heat management
- · Traditional urban planning methods
Improved AI models for urban shade simulation become more accessible and accurate.
Better urban planning and infrastructure development leads to more livable and climate-resilient cities.
Reduced public health risks associated with urban heat exposure and increased economic activity in comfortable outdoor spaces.
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Read at arXiv cs.AI