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Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

by Douglas A Stow, Allen Hope, David McGuire, David Verbyla, John Gamon, Fred Huemmrich, Stan Houston, Charles Racine, Matthew Sturm, Kenneth Tape, Larry Hinzman, Kenji Yoshikawa, Craig Tweedie, Brian Noyle, Cherie Silapaswan, David Douglas, Brad Griffith, Gensuo Jia, Howard Epstein, Donald Walker, Scott Daeschner, Aaron Petersen, Liming Zhou, Ranga Myneni show all authors
Remote Sensing of Environment ()

Abstract

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation LandAirIce Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations. The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

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