Source: Alec Foster, Ian M. Dunham, and Charles Kaylor, “Citizen Science for Urban Forest Management? Predicting the Data Density and Richness of Urban Forest Volunteered Geographic Information,” Urban Science
Ann Arbor, MI (September 19, 2017) – Volunteered geographic information (VGI) has been heralded as a promising new data source for urban forest planning and policymaking. But can it succeed with uneven levels of participation and spatial coverage?
To begin addressing these concerns, new research examines the spatial distribution and data richness of urban forest VGI in Philadelphia, Pennsylvania and San Francisco, California.
Using ordinary least squares (OLS), general linear models (GLM), and spatial autoregressive models, the research findings reveal that sociodemographic and environmental indicators are strong predictors of both densities of attributed trees and data richness.
Although recent digital urban tree inventory applications present significant opportunities for collaborative data gathering, innovative research, and improved policymaking, asymmetries in the quantity and quality of the data may undermine their effectiveness. If these incomplete and uneven datasets are used in policymaking, environmental justice issues may arise.