Urban forest structure effects on property value (2015)
Studies have quantified urban forests using well established field sampling methods. Other studies have used hedonic regression with real estate prices and remotely sensed vegetation cover data in valuation models. However, remote sensing introduces unfamiliar perspectives since it changes the scale and resolution perceived by humans. Real estate prices also fluctuate and are not regularly used in urban decision-making processes. This study values an urban forest cultural ecosystem service by integrating an explanatory hedonic regression model with randomly field-measured tree, shrub, and turf data from four cities across Florida, USA, during 2006–2009, and congruent parcel tract-level home attributes and appraised property values from single and multi-family units for 2008–2009. Results, on average, indicate trade-offs in that more trees with greater Leaf Area Indices (LAIs) add to property value, while biomass and tree–shrub cover have a neutral effect, and replacing tree with grass cover has lower value. On average, property value increased by $1586 per tree and $9348 per one-unit increase in LAI, while increasing maintained grass from 25% to 75% decreased home value by $271. Our ecological approach is an alternative, applied method that can be used by decision-makers for policy and cost–benefit analyses that calculate the stream of net benefits associated with urban forests.