Green Infrastructure (GI) is a critical element of urban sustainability that provides environmental, economic, and social benefits. Adoption, however, has been slow. It is critical to demonstrate the paybacks in localized contexts to encourage uptake (European Commission, 2021; Matthews et al., 2015).

Hedonic pricing models (HPM) are a method of regression that isolate physical and spatial characteristics of property to estimate the impact on valuation (Monson, 2009). This method is used to evaluate how proximity to GI such as parks, coastlines, and forests impact real estate markets. Although HPMs have been deployed for on-site features such as balconies and floor levels, very few have assessed on-site GI.

This dissertation investigates the impact of on-site GI on apartment listing prices in Helsinki, Finland through an HPM. Taking into account local real estate practices and urban form, a structural characteristics index was created. A multi-linear regression was then conducted on a dataset collected from 200 property listings to measure the relationship between the structural characteristics and property listing prices.

Although the model was overfit (requiring a larger sample), several significant findings were discovered. For each unit increase, the apartment listings gained or lost the following in value: square metre of living area (+€8,079), bathroom (+€101,040), floor level (+€7,928), each km away from the coastline (-€15,080), each km away from the central business district (-€14,277), landscape gardening (+€79,250). No finding produced statistically significant evidence against the hypothesis (that GI has a positive association with apartment listing valuation).

These findings offer practical applications for the real estate industry. Strategies can be crafted to maximize apartment valuation by recognizing proximity to certain features and on-site landscape gardening. The findings support the notion that spatial and on-site GI increase property valuation.