Using Satellite Remote-Sensing in Landscape-Scale Wildlife and Ecological Process Studies in Terrestrial and Marine Areas of northern North America
This project serves as a focal point of capability and expertise for integrating remote sensing, satellite telemetry and GIS. Working collaboratively with other principal investigators, this project applies satellite and software technologies to study spatial and temporal interactions between wildlife populations and their environment. There are three primary objectives: 1) develop optimal structures for wildlife distribution databases with emphasis on satellite tracking data; 2) develop environmental thematic databases with emphasis on Arctic regions; and 3) develop GIS algorithms for integrated data analyses.
Commensurate with accelerating advances in remote sensing, satellite telemetry, and geographic information system (GIS) technology, the primary objective of this task is to evaluate and apply these state-of-the-art tools for developing or improving the methodologies used in wildlife and ecosystem research. The need for cost-effective techniques to systematically acquire environmental data for remote or inaccessible areas, and locational data for highly mobile or migratory species, crosses bureau, program and issue boundaries. This is especially true in arctic regions, where numerous fish and wildlife populations often range internationally, across extensive landscapes of tundra, boreal forest, polar sea-ice, and aquatic ecosystems. Remote sensing technologies provide alternatives to traditional sampling methods, which are typically too expensive to implement across large spatial scales or severely compromised by hazardous weather conditions and extended winter darkness.
Publications: Douglas, D.C., 2010, Arctic sea ice decline: Projected changes in timing and extent of sea ice in the Bering and Chukchi Seas: U.S. Geological Survey Open-File Report 2010-1176, 32 p.
Belchansky, G. I., D. C. Douglas, and N. G. Platonov (2005), Spatial and temporal variations in the age structure of Arctic sea ice, Geophys. Res. Lett.,32, L18504, doi:10.1029/2005GL023976
Belchanksy, G. I., D. C. Douglas, I. N. Mordvintsev, and N. G. Platonov (2004), Estimating the time of melt onset and freeze onset over Arctic sea-ice area using active and passive microwave data. Remote Sens. Environ., 92 , 21-39.
Belchansky, G. I., D. C. Douglas, and N. G. Platonov (2004), Duration of the Arctic sea ice melt season: Regional and interannual variability, 1979-2001, J. Climate, 17 , 67-80.
Belchansky, G. I., D. C. Douglas, I. V. Alpatsky, and N. G. Platonov (2004) , Spatial and temporal multiyear sea ice distributions in the Arctic : A neural network analysis of SSM/I data, 1988-2001, J. Geophys. Res. , 109 (C12), doi:10.1029/2004JC002388. Stone, R. S., D. C. Douglas, G. I. Belchansky, S. D. Drobot, and J. Harris (2005), Cause and effect of variations in western Arctic snow and sea ice cover. 8.3, Proc. Am. Meteorol. Soc. 8 th Conf. on Polar Oceanogr. and Meteorol. , San Diego , CA , 9-13 January.
Belchansky, G. I., D. C. Douglas, V. A. Eremeev, and N. G. Platonov (2005), Variations in the Arctic's multiyear sea ice cover: A neural network analysis of SMMR-SSM/I data, 1979-2004. Geophys. Res. Lett. Vol. 32, No. 9, L09605, doi:10.1029/2005GL022395.
Stone, R. S., D. C. Douglas, G. I. Belchansky, and S. D. Drobot (2005), Polar climate: Arctic sea ice, Pages 39-41 in D. H. Levinson (ed.), State of the Climate in 2004, Bull. Amer. Meterol. Soc., Vol. 86, No. 6, 86 pp. Stone, R. S., D. C. Douglas, G. I. Belchansky, and S. D. Drobot (2005), Correlated declines in western Arctic snow and sea ice cover. Arctic Res. United States, 19:18-25.
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