Keywords

Advanced Microwave Instrument, C-band European Remote Sensing satellite, Greenland, NASA Scatterometer, azimuth angle, climate change, ice sheet, water, incidence angle, intraannual variations, microwave signature, observation geometry, radar backscatter, scatterometer mode, snow facies, snow surface, spatial gradient, synthetic aperture radar

Abstract

Characterization of the microwave signature of the Greenland snow surface enables delineation of the different snow facies and is a tool for tracking the effects of climate change. A new empirical observation model is introduced that uses a limited number of parameters to characterize the snow surface based on the dependence of radar backscatter on incidence angle, azimuth angle, spatial gradient, and temporal rate of change. The individual model parameters are discussed in depth with examples using data from the NASA Scatterometer (NSCAT) and from the C-band European Remote Sensing (ERS) satellite Advanced Microwave Instrument in scatterometer mode. The contribution of each model term to the overall accuracy of the model is evaluated. The relative contributions of the modeled dependencies vary by region. Two studies illustrating applications of the model are included. First, interannual changes over the Greenland ice sheet are investigated using nine years of ERS data. Surface changes are observed as anomalies in the σ˚ model parameters. Second, intraannual variations of the surface are investigated. These changes are observed in the average backscatter normalized to a given observation geometry. The results indicate that the model can be used to obtain a more complete understanding of multiyear change and to obtain low-variance high temporal resolution observations of intraannual changes. The model may be applied for increased accuracy in scatterometer, synthetic aperture radar (SAR), and wide-angle SAR studies.

Original Publication Citation

Ashcraft, I. S., and D. G. Long. "Observation and Characterization of Radar Backscatter Over Greenland." Geoscience and Remote Sensing, IEEE Transactions on 43.2 (25): 225-37

Document Type

Peer-Reviewed Article

Publication Date

2005-02-01

Permanent URL

http://hdl.lib.byu.edu/1877/1086

Publisher

IEEE

Language

English

College

Ira A. Fulton College of Engineering and Technology

Department

Electrical and Computer Engineering

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