GeoEstateChat is a research project exploring how LLMs can enhance the interaction between geospatial analysis and real-estate decision-making. The project studies LLMs as analytical intermediaries that translate natural-language questions into structured, multi-scale geospatial queries, rather than as sources of knowledge.

Geospatial analysis tools are characterized by high analytical complexity and flexibility but low usability, making them largely exclusive to domain experts, while most real-estate platforms prioritize usability at the cost of analytical depth, typically offering only basic attributes such as location and price. By integrating an LLM-driven reasoning layer with a deterministic geospatial backend, GeoEstateChat investigates how user intent, spatial scale, data filtering, and analytical logic can be inferred from ambiguous human language, enabling both high complexity and high usability within a single system. The research focuses on reducing the technical barriers of GIS while preserving analytical rigor, transparency, and reproducibility.

GeoEstateChat positions LLMs as a new infrastructural layer for geospatial research, examining their potential to reshape access, workflow design, and decision-support processes in urban and real-estate contexts.

The project aims to answer below questions.