Temporal Decorrelation Studies Relevant for a Vegetation InSAR Mission
Paul
Siqueira, University of Massachusetts, siqueira@ecs.umass.edu
(Presenting)
Bruce
Chapman, Jet Propulsion Laboratory, bruce.chapman@jpl.nasa.gov
Scott
Hensley, Jet Propulsion Laboratory, sh@radar-sci.jpl.nasa.gov
Kathleen
Bergen, University of Michigan, kbergen@umich.edu
For mapping vegetation 3-dimensional structure, there are currently two principal methods. One method is to use full waveform lidar to map the canopy reflective properties as a function of range within the illuminated spot of the lidar. The second method is to use radar interferometry to collect the spatial frequencies which are used to estimate the 3-D structure of vegetation canopies over the radar swath. A realistic scenario for implementing a spaceborne 3-D structure mapping mission will likely include some combination of these two technologies, thus making best use of the high resolving power of the lidar measurements while benefiting from the all weather and wide swath coverage of the SAR observations. Because of dimensional and orbital constraints, the InSAR portion of such a mission would likely use a repeat-pass observing strategy to measure the interferometric response of vegetation one spatial frequency at a time. In this observing scenario, the change of the target’s geometry over time would be the principal error source in determining the vegetation 3-D structure. In this poster we discuss early results from existing airborne and satellite data for quantifying temporal decorrelation at L-band and P-band and present observing strategies which can be implemented in a spaceborne mission. By continuing this study of temporal decorrelation and quantifying its affect on 3-D structure estimation, we will provide critical information for designing a mission to make these measurements from a spaceborne platform.