Date of Award

12-17-2000

Document Type

Thesis

Abstract

Vegetation on the Seward Peninsula, Alaska, which is characterized by transitions from tundra to boreal forest, may be sensitive to the influences of climate change on disturbance and species composition. To determine the ability to detect decadal-scale structural changes in vegetation, Change Vector Analysis (CVA) techniques were evaluated for Landsat TM imagery of the Seward Peninsula. Scenes were geographically corrected to sub-pixel accuracy and then radiometrically rectified. The CVA results suggest that shrubbiness is increasing on the Seward Peninsula. The CVA detected vegetation change on more than 50% of the burned region on TM imagery for up to nine years following fire. The use of both CVA and unsupervised classification together provided a more powerful interpretation of change than either method alone. This study indicates that CVA may be a valuable tool for the detection of land-cover change in transitional regions between tundra and boreal forest.

Handle

http://hdl.handle.net/11122/6682

Share

COinS