Recommended Citation
August 1, 2012.
Abstract
This project focuses on implementing a software component that will help the NASA JPL (Jet Propulsion Laboratory) UAVSAR (Uninhabited Ariel Vehicle Synthetic Aperture Radar) group ultimately estimate Earth’s biomass and vegetation properties. Estimating the worldwide biomass will contribute to our understanding of the changing climate. By utilizing Cloude’s model-based incoherent decomposition we are able to extract the maximum surface-to-volume scattering ratio from the polarimetric and interferometric SAR (Pol-InSAR) data. The surface-to-volume ratio contains information about the structure of the imaged vegetated area, and can be used to detect vegetation changes between data acquisitions. The software component will create an image mask using a threshold based on the surface-to-volume ratio. The mask will be needed at times when vegetation changes between data acquisitions are too large to allow for accurate estimation of forest parameters from Pol-InSAR data. In order to implement the mask, we implemented the mathematical model in C programming language and incorporated it into the parameter estimation program. In the presentation we will describe the theoretical model and show results of the estimation surface-to-volume ratio on using UAVSAR collected over the Harvard Forest (MA).
Mentor
Marco Lavalle Ph.D.
Lab site
NASA Jet Propulsion Laboratory (JPL)
Funding Acknowledgement
This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation. This project has also been made possible with support of the National Marine Sanctuary Foundation. The STAR program is administered by the Cal Poly Center for Excellence in Science and Mathematics Education (CESaME) on behalf of the California State University (CSU).
URL: https://digitalcommons.calpoly.edu/star/153