Characterization of Surrounding Greenery and Housing Prices Using Street View Images Across Urban Local Climate Zones and Cities of Metro Manila

Abstract. Urban greenery is increasingly recognized as a factor that can influence residential property values. Despite this, few studies have explored this relationship using street-level perspectives or across diverse urban forms in developing megacities like Metro Manila. This study examines the relationship between visible greenery and housing prices in Metro Manila, utilizing Google Street View images sampled at 100-meter intervals and processed through a PSPNet-based semantic segmentation model pretrained on the ADE20K dataset to calculate the Green View Index (GVI). GVI values were averaged within 400-meter radius buffers around 1007 housing units sourced from Lamudi, with an 80-20 train-test split. Spatial autocorrelation analyses (Getis-Ord Gi* and Local Moran’s I) identified heterogeneous clusters of greenery and housing prices across the region. Hedonic pricing models, incorporating structural/housing attributes, location, proximity to amenities, facility density, and GVI, were estimated at three scales: the entire Metro Manila area, eight urban Local Climate Zones (LCZs), and individual cities. In the overall Metro Manila model, GVI exhibited a positive association with housing prices, suggesting that higher visible greenery generally enhances property values. However, this effect varied across LCZ-based and city-based analyses: GVI significantly increased prices in open mid-rise (LCZ 5) and open low-rise (LCZ 6) areas, as well as in urbanized centers like Makati and Manila, while showing negligible impact in compact and mixed-built zones. These findings underscore the value of context-specific urban greening to boost property values and inform sustainable planning in Metro Manila.