Climate intervention ABM for evaluating shade and cooling strategies on La Rambla, Barcelona | Exea Impact × Aretian
A multi-AI-agent system that maps urban heat zones and simulates shade deficits to prioritize tree-planting locations, built with Google ADK (Gemini 2.5 Flash), FastAPI, Google Earth Engine, and Next.js.
Idées et travaux ouverts pour un rafraîchissement urbain durable, inspirés des glacières anciennes — au service de la résilience et de l'avenir.
Open-source, screening-level decision support for evaluating and prioritising nature-based solutions for urban cooling — literature-grounded scores, transparent cited methodology, offline-first map, PDF/XLSX reports. A Criterra product.
Geospatial AI/ML platform backed by Physics-Informed Machine Learning (PIML) to map urban heat stress hotspots, quantify thermal drivers (NDVI, Albedo, Building Density), and run scenario-based spatial optimization for urban cooling interventions.
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