B44A-07:
The Role of Remote Sensing in Modeling Landscape Change and Its Associated Carbon Cycle Impacts Across Terrestrial Arctic Ecosystems

Thursday, 18 December 2014: 5:30 PM
Daniel J Hayes1, Santonu Goswami1, Benjamin M Jones2, Guido Grosse3, Andrew Balser4 and Stan D Wullschleger1, (1)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (2)USGS Alaska Science Center, Anchorage, AK, United States, (3)Alfred Wegener Institute Helmholtz-Center for Polar and Marine Research Potsdam, Potsdam, Germany, (4)University of Alaska Fairbanks, Fairbanks, AK, United States
Abstract:
Terrestrial ecosystems across the circumpolar Arctic region are undergoing unprecedented changes in structure and function as a result of rapid climate warming. Such changes have substantially altered energy, water and biogeochemical cycling in these regions, which has important global-scale consequences for climate and society. Recognizing the vulnerability of these ecosystems to change, scientists and decision-makers have identified a critical need for research that employs existing and new remote sensing technologies and methodologies to observe, monitor and understand changes in Arctic ecosystems. The unique capabilities provided by remote sensing imagery and data products have allowed us novel views of ecosystems and their dynamics over multiple scales in time and space across all regions of the globe. Here we offer a synthetic discussion of the recent and emerging science focused on understanding the dynamic landscape processes in Arctic terrestrial ecosystems using a variety of remotely-sensed information collected from passive and active sensors on ground-, aircraft- and satellite- based platforms. To consider the evolution of these technologies, methods and applications over recent decades, we look at key examples from the scientific literature that range from the use of radar sensors for local-scale characterization of active layer dynamics to the circumpolar-scale assessment of changes in vegetation productivity using long-term records of optical satellite imagery. This discussion has a particular focus on the use of remotely sensed data and products to parameterize, drive, evaluate and benchmark the modeling of Arctic ecosystem processes. We use these examples to demonstrate the opportunities for model-data integration, as well as to highlight the challenges of remote sensing studies in northern high latitude regions.