Relationships between tree rings and Landsat EVI in the Northeast United States

• Main Author: Farina, Mary K.
• Language: en_US
• Published: 2016
• Subjects: Remote sensing; Carbon uptake in temperate forests; Dendrochronology; Landsat; Tree ring width; Vegetation productivity; Enhanced vegetation Index
• Online Access: https://hdl.handle.net/2144/15277

Changes in the productivity of temperate forests have important implications for atmospheric carbon dioxide (CO2) concentrations, and many efforts have focused on methods to monitor both gross and net primary productivity in temperate forests. Remotely sensed vegetation indices provide spatially extensive measures of vegetation activity, and the Enhanced Vegetation Index (EVI) has been widely linked to photosynthetic activity of vegetation. Networks of tree ring width (TRW) chronologies provide ground-based estimates of annual net carbon (C) uptake in forests, and time series of EVI and TRW may capture common productivity signals. Robust correlations between mean TRW and EVI may enhance spatial extrapolations of TRW-based productivity estimates, ultimately improving understanding of spatio-temporal variability in forest productivity. The research presented in this thesis investigates potential empirical relationships between networks of TRW chronologies and time series of Landsat EVI and Landsat-based phenological metrics in the Northeast United States. We hypothesized that mean TRW is positively correlated with mean monthly EVI during the growing season, EVI integrated over the growing season, and growing season length. Results indicate that correlations between TRW and EVI are largely not significant in this region. The complex response of tree growth to a variety of limiting climatic factors in temperate forests may decouple measures of TRW growth and canopy reflectance. However, results also indicate that there may be important lag effects in which EVI affects mean TRW during the following year. These findings may improve understanding of links between C uptake and growth of tree stems over large spatial scales.