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Proceedings Paper

The sensitivity of RADARSAT-2 quad-polarization SAR data to crop LAI
Author(s): Xianfeng Jiao; Heather McNairn; Jiali Shang; Elizabeth Pattey; Jiangui Liu; Catherine Champagne
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Paper Abstract

The object of this paper is to investigate the relationship between polarimetric SAR information and LAI. RADARSAT- 2 Fine Quad-pol SLC data with shallower and steeper incidence angles were programmed throughout the 2008 growing season. Optical data were acquired using a hyperspectral CASI airborne sensor as well as the SPOT-4 multi-spectral satellite. The optical data were used to generate LAI map for the entire study site. Backscatter coefficients, ratios of backscatter intensity, three polarimeric variables and three Cloude-pottier Decomposition parameters were extracted from the polarimetric data set. Temporal variations of the backscatter coefficient were analyzed. The results show an increase in backscatter with corn and soybean growth. The statistical analysis quantified the relationship between the radar parameters and LAI revealing a strong sensitivity for some radar configurations. For both corn and soybean, RADARSAT-2 cross-polarization (HV) backscatter at either shallow or steep incidence angles was well correlated with LAI. To avoid sensitivity to sensor calibration and changing target moisture conditions, ratios of backscatter intensity, polarimetric variables and Cloude-pottier Decomposition parameters were investigated. For corn, the ratio of HV/HH and HV/VV as well as pedestal height, total power, correlation coefficient, Entropy and alpha angle were highly correlation with LAI at steeper incidence angle. For soybean, the higher correlations were found with the ratio of HV/HH as well as pedestal height, total power, Entropy and alpha angle at shallow incidence angle. In general, the best results were observed for corn using the FQ6 acquisition. For soybean, the FQ20 data provided the most promising results.

Paper Details

Date Published: 21 August 2009
PDF: 11 pages
Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 74540O (21 August 2009); doi: 10.1117/12.825701
Show Author Affiliations
Xianfeng Jiao, Agriculture and Agri-Food Canada (Canada)
Heather McNairn, Agriculture and Agri-Food Canada (Canada)
Jiali Shang, Agriculture and Agri-Food Canada (Canada)
Elizabeth Pattey, Agriculture and Agri-Food Canada (Canada)
Jiangui Liu, Agriculture and Agri-Food Canada (Canada)
Catherine Champagne, Agriculture and Agri-Food Canada (Canada)


Published in SPIE Proceedings Vol. 7454:
Remote Sensing and Modeling of Ecosystems for Sustainability VI
Wei Gao; Thomas J. Jackson, Editor(s)

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