Authors: Shira Ellenson*, University of Montana, Anna Klene, University of Montana
Topics: Cryosphere, Remote Sensing, Biogeography
Keywords: Arctic, climate change, remote sensing, photogrammetry, tundra
Session Type: Virtual Poster
Start / End Time: 8:00 AM / 9:15 AM
Room: Virtual 51
Presentation File: Download
As the Arctic warms, vegetation is responding with changes in species composition, density, and distribution. Remote sensing is being used to summarize broad Arctic trends, but more work is needed at the plot-level to elucidate complex ecosystem interactions. To help address these issues, this study investigates image-based point cloud data to estimate vegetation canopy cover. Color-infrared (CIR) aerial photographs were obtained of Toolik Lake, Alaska at 1:3000 resolution in August 1995. Photogrammetry software was utilized to develop high density point clouds of the 1-hectare plot and surroundings. Historic markers were used as ground controls points (GCPs) to tie the resultant elevation products to an established vertical datum and validate vertical accuracies. The resulting point cloud was classified as ground/non-ground points and used to generate a digital surface model (DSM) and digital terrain model (DTM). Differences in the interpolated DTM and DSM yield tundra canopy height estimates. The estimates were then compared to existing field notes from 1995 of vegetation species and height. The DTM and DSM serve as a baseline of historic vegetation characteristics to which future measurements can be compared. Pairing modern photogrammetric techniques with historic aerial photos may prove to be valuable for studying long-term change.