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Appl. Sci. 2017, 7(6), 602; doi:10.3390/app7060602

A Multi-Year Study on Rice Morphological Parameter Estimation with X-Band Polsar Data

1
Institute of Environmental Engineering ETH Zurich, 8093 Zurich, Switzerland
2
Faculty of Civil Engineering, Istanbul Technical University, 34469 Istanbul, Turkey
3
Microwaves and Radar Institute, German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Carlos López-Martínez and Juan Manuel Lopez-Sanchez
Received: 29 March 2017 / Revised: 24 May 2017 / Accepted: 8 June 2017 / Published: 9 June 2017
(This article belongs to the Special Issue Polarimetric SAR Techniques and Applications)
View Full-Text   |   Download PDF [3182 KB, uploaded 13 June 2017]   |  

Abstract

Rice fields have been monitored with spaceborne Synthetic Aperture Radar (SAR) systems for decades. SAR is an essential source of data and allows for the estimation of plant properties such as canopy height, leaf area index, phenological phase, and yield. However, the information on detailed plant morphology in meter-scale resolution is necessary for the development of better management practices. This letter presents the results of the procedure that estimates the stalk height, leaf length and leaf width of rice fields from a copolar X-band TerraSAR-X time series data based on a priori phenological phase. The methodology includes a computationally efficient stochastic inversion algorithm of a metamodel that mimics a radiative transfer theory-driven electromagnetic scattering (EM) model. The EM model and its metamodel are employed to simulate the backscattering intensities from flooded rice fields based on their simplified physical structures. The results of the inversion procedure are found to be accurate for cultivation seasons from 2013 to 2015 with root mean square errors less than 13.5 cm for stalk height, 7 cm for leaf length, and 4 mm for leaf width parameters. The results of this research provided new perspectives on the use of EM models and computationally efficient metamodels for agriculture management practices. View Full-Text
Keywords: polarimetry; SAR; precision agriculture; rice monitoring; stochastic optimization; metamodels; radiative transfer models; electromagnetic scattering models polarimetry; SAR; precision agriculture; rice monitoring; stochastic optimization; metamodels; radiative transfer models; electromagnetic scattering models
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Yuzugullu, O.; Erten, E.; Hajnsek, I. A Multi-Year Study on Rice Morphological Parameter Estimation with X-Band Polsar Data. Appl. Sci. 2017, 7, 602.

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