CVDec 16, 2025

EcoScapes: LLM-Powered Advice for Crafting Sustainable Cities

arXiv:2512.14373v1h-index: 6Has Code
Originality Synthesis-oriented
AI Analysis

This addresses climate adaptation challenges for small cities, but it is incremental as it builds on existing technologies like LLMs and satellite analysis.

The paper tackles the problem of small cities struggling with limited personnel and data integration for climate adaptation by proposing a multi-layered system combining specialized LLMs, satellite imagery, and a knowledge base, resulting in a tool that aids in developing effective strategies.

Climate adaptation is vital for the sustainability and sometimes the mere survival of our urban areas. However, small cities often struggle with limited personnel resources and integrating vast amounts of data from multiple sources for a comprehensive analysis. To overcome these challenges, this paper proposes a multi-layered system combining specialized LLMs, satellite imagery analysis and a knowledge base to aid in developing effective climate adaptation strategies. The corresponding code can be found at https://github.com/Photon-GitHub/EcoScapes.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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