Four decades of urban land cover change in Philadelphia

Abstract

Given ambitious tree canopy goals, land cover change analyses in cities are imperative. Urban tree canopy change analyses have been hindered by data with low categorical resolution (e.g., canopy vs. not canopy), over relatively short time horizons (5–10 years), representing only two points in time, and scarce linkages to other temporal datasets (e.g., historical socioeconomic data). In this study, using a land cover change data set with five cover classes spanning 40 years (1970–2010) for Philadelphia, PA (US), we asked: which types of land cover changes are most common, and how do those relate to and co-vary with socioeconomic change? Specifically, we tabulated land cover changes (i.e., transition sequences), applied multinomial logistic regression with socioeconomic variables as predictors of land cover change, and used cluster analyses to characterize neighborhood changes associated with land cover change. Land cover stability dominated the transition sequences: the four most common sequences were stable road (e.g. road-road-road-road-road), stable building, tree canopy, and herbaceous vegetation, collectively accounting for 62.57% of all sequences. Multinomial logistic regression identified that increases in homeownership, income, and educational attainment were associated with a higher probability of tree canopy persistence. Cluster analyses via Affinity Propagation showed that some Census tracts have similar land cover change trajectories, and yet different socioeconomic trends. These findings point towards opportunities to focus on tree preservation alongside the importance of establishing new tree canopy through planting. Our study demonstrates the mix of stability and dynamism in multidecadal urban land cover change, and the importance of connecting land cover changes with socioeconomic changes.