Inter-annual Variability in Tundra Phenology Captured with Digital Photography

The need to improve multi-scale phenological monitoring of arctic terrestrial ecosystems has been a persistent research challenge. Although there has been a range of advances in remote sensing capacities over the past decade, these present costly, and sometimes logistically challenging and technically demanding solutions for arctic terrestrial ecosystems. In this poster and undergraduate research project, we demonstrate how seasonal and inter-annual variability in landscape phenology can be derived for multiple tundra ecosystems using a low-cost and low-tech kite aerial photography (KAP) system that has been developed as a contribution to the US Arctic Observing Network. Seasonal landscape phenology was observed over the Networked Info-Mechanical Systems (NIMS) grids (2 x 50 meters) located in Barrow and Atqasuk, Alaska using imagery acquired with KAP and analyzed for a range of greenness indices. Preliminary results showed that the 2G-RB greenness index correlated the best with NDVI values calculated from ground based hyperspectral reflectance measurements. 2012 had the highest 2G-RB greenness index values for both Barrow and Atqasuk sites, which correlated well with NDVI values acquired from ground-based hyperspectral reflectance measurements. Wet vegetation types showed the most interannual variability at the Atqasuk site based on the 2G-RB greenness index while in Barrow the moist vegetation types showed the most interannual variability. These results show that vegetation indices similar to those acquired from hyperspectral remote sensing platforms can be derived using low-cost and low-tech techniques. Further analysis using these same techniques is required in order to link relatively small scale vegetation dynamics measured with KAP with those documented at large scales using satellite imagery.