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Journal of Applied Remote Sensing

Leaf area index estimation of lowland rice using semi-empirical backscattering model
Author(s): Vineet Kumar; Mamta Kumari; Sudip Kumar Saha
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Paper Abstract

Rice crop monitoring using synthetic aperture radar (SAR) polarimetry is one of the thrust areas of research in radar remote sensing due to unavailability of optical data in critical growth stages of crop because of dense cloud cover during the growing season (monsoon) in India and Southeast Asia. The prime objective of this study was to assess the potential of polarimetric C-band SAR data to estimate the leaf area index (LAI) of two varieties (non-basmati and basmati) of paddy rice. Seven fine Quad-pol single look complex (SLC) RADARSAT-2 data were acquired over part of the Indo-Gangetic plain, India, in 2011 and 2012, and ground data were collected during the same period of the satellite pass. The backscatter of rice in different polarizations over different growth periods was analyzed and LAI estimated using a semi-empirical model. The performance of the model was evaluated by statistical parameters, namely. root mean square error and coefficient of determination (R2 ). The model performed well for the LAI estimation of non-basmati rice using HV backscatter while achieving acceptable accuracy for others. Results of this study provided the promising approach for LAI prediction using SAR data in India.

Paper Details

Date Published: 26 November 2013
PDF: 11 pages
J. Appl. Remote Sens. 7(1) 073474 doi: 10.1117/1.JRS.7.073474
Published in: Journal of Applied Remote Sensing Volume 7, Issue 1
Show Author Affiliations
Vineet Kumar, Indian Institute of Remote Sensing (India)
Mamta Kumari, Indian Institute of Remote Sensing (India)
Sudip Kumar Saha, Indian Institute of Remote Sensing (India)

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