FURI | Spring 2026

Investigating the Correlation Between Urban Greenspace and Mental Health Through Geospatial and NLP Analysis

Urbanization shapes many aspects of city life, including the emotional wellbeing of residents. The level of greenery in a given area, quantified by the Normalized Difference Vegetation Index (NDVI), is a meaningful factor in city planning and access to higher levels has been linked to alleviate stress and anxiety. Pre-existing studies suggest this correlation; however, most are reliant on surveys, questionnaires, and traditional methods of data collection. This project maps vegetation density, using artificial intelligence to interpret sentiment from geo-tagged posts and local reviews, and models the correlation. Natural language processing  (NLP) model BERT-based sentiment classifiers were applied to analyze tone and extract indicators of psychological wellbeing. The two datasets were “spatially joint” to NDVI coordinate maps of multiple cities and analyzed using regression modeling to evaluate whether vegetation density meaningfully predicted sentiment patterns. While there exists no statistically significant relationship between the two datasets, this research addresses the effect of urban environments on mental health, providing  insight on urban planning, public health, and equitable access to greenspace.