Assessment of urban tree growth from structure, nutrients and composition data derived from airborne lidar and imaging spectroscopy

Abstract:

Urban forests provide important ecosystem services related to climate, nutrients, runoff and aesthetics. Assessment of variations in urban forest growth is critical to urban management and planning, as well as to identify responses to climate and other environmental changes. We estimated annual relative basal area increment by tree rings from 37 plots in Madison, Wisconsin and neighboring municipalities. We related relative basal area growth to variables of vegetation traits derived from remote sensing, including structure (aboveground biomass, diameter, height, basal area, crown width and crown length) from discrete-return airborne lidar, and biochemical variables (foliar nitrogen, carbon, lignin, cellulose, fiber and LMA), spectral indices (NDVI, NDWI, PRI, NDII etc.) and species composition from AVIRIS hyperspectral imagery. Variations in tree growth was mainly correlated with tree species composition (R² = 0.29, RMSE = 0.004) with coniferous stands having a faster growth rate than broadleaf plots. Inclusion of stand basal area improved model prediction from R² = 0.29 to 0.35, with RMSE = 0.003. Then, we assessed the growth by functional type, we found that foliar lignin concentration and the proportion of live coniferous trees explained 57% variance in the growth of conifer stands. In contrast, broadleaf forest growth was more strongly correlated with species composition and foliar carbon (R² = 0.59, RMSE = 0.003). Finally, we compared the relative basal area growth by species. In our study area, red pine and white pine exhibited higher growth rates than other species, while white oak plots grew slowest. There is a significant negative relationship between tree height and the relative growth in red pine stands (r = -0.95), as well as a strong negative relationship between crown width and the relative growth in white pine stands (r = -0.87). Growth declines as trees grow taller and wider may partly be the result of reduced photosynthesis and water availability. We also found that canopy cellulose content was negatively correlated with growth in white oak (r = -0.59), which could be caused by trade off of carbon allocation from shoot storage to leaves. These results demonstrate the potential of lidar and hyperspectral imagery to characterize important traits associated with biomass accumulation in urban forests.