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Comparison of Decomposition Methods over Agricultural Fields Using the UAVSAR Polarimetric Synthetic Aperature Radar
Paper ID : 1394-SMPR
Authors:
Ehsan Kiana *1, Saeid Homayouni2, Mohammad Ali Sharifi3, Mohamadreza Faridrohani4
1School of Surveying and Geospatial Engineering, Dept. of Remote Sensing, College of Engineering, U. of Tehran, Iran
2Centre Eau Terre Environnement, Institut National de la Recherche Scientifique, Quebec, Canada
3Research Institute of Geoinformation Technology, School of Surveying and Geospatial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran
4Faculty of mathematical Sciences, Dept. of Statistics, Shahid Beheshti University, Iran
Abstract:
This paper investigates and compares the potential of five model-based polarimetric decompositions, namely those developed by Eignvector-based decomposition (Van Zyle), Model-based decomposition (Freeman-Durden three-component decomposition and Yamaguchi four-component decomposition), An & Yang3 and An & Yang4 for crop biomass detection over agricultural fields covered by various crops. The time series of Unihabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data and the ground thruth of soil and vegetation characteristics collected during the Soil Moisture Active Passive (SMAP) Validation Experiment in 2012 (SMAPVEX12) were used to compare the five decomposition methods with related to the scattering mechanisms and the biomass retrieval performances. The results show that the performance of each decomposition method for biomass retrieval depends on the crop types and the crop phonological stages. Finally, an overall biomass underestimation was observed from the five decompositions, and the highest regression value of 99% was obtained from Freeman decomposition as a result of the enhanced volume scattering. Indeed, Freeman-Durden model provided the best results.
Keywords:
Biomass, Agricultural fields, Polarimetric decomposition, Ground measurements, UAVSAR
Status : Conditional Accept (Poster)