A visual-semantic spatiotemporal framework creates the Street Economic Vitality Index (SEVI) to diagnose urban street economic vitality by parsing streetscapes with AI, standardizing brands via VLM-LLM, and incorporating lagged LBS demand data with Gaussian spillover modeling.
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Diagnosing Urban Street Vitality via a Visual-Semantic and Spatiotemporal Framework for Street-Level Economics
A visual-semantic spatiotemporal framework creates the Street Economic Vitality Index (SEVI) to diagnose urban street economic vitality by parsing streetscapes with AI, standardizing brands via VLM-LLM, and incorporating lagged LBS demand data with Gaussian spillover modeling.