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Remote Sens. 2017, 9(5), 460; doi:10.3390/rs9050460

Determining Rice Growth Stage with X-Band SAR: A Metamodel Based Inversion

1
Institute of Environmental Engineering, ETH Zurich, 8093 Zürich, Switzerland
2
Institute of Civil Engineering, ETH Zurich, 8093 Zürich, Switzerland
3
Faculty of Civil Engineering, Istanbul Technical University, Istanbul 34469, Turkey
4
Microwaves and Radar Institute, German Aerospace Center (DLR), 82234 Oberpfaffenhofen, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Klaus Scipal and Prasad S. Thenkabail
Received: 30 March 2017 / Revised: 26 April 2017 / Accepted: 3 May 2017 / Published: 10 May 2017
(This article belongs to the Special Issue Recent Advances in Polarimetric SAR Interferometry)
View Full-Text   |   Download PDF [9335 KB, uploaded 12 May 2017]   |  

Abstract

Rice crops are important in the global food economy, and new techniques are being implemented for their effective management. These techniques rely mainly on the changes in the phenological cycle, which can be investigated by remote sensing systems. High frequency and high spatial resolution Synthetic Aperture Radar (SAR) sensors have great potential in all-weather conditions for detecting temporal phenological changes. This study focuses on a novel approach for growth stage determination of rice fields from SAR data using a parameter space search algorithm. The method employs an inversion scheme for a morphology-based electromagnetic backscattering model. Since such a morphology-based model is complicated and computationally expensive, a surrogate metamodel-based inversion algorithm is proposed for the growth stage estimation. The approach is designed to provide estimates of crop morphology and corresponding growth stage from a continuous growth scale. The accuracy of the proposed method is tested with ground measurements from Turkey and Spain using the images acquired by the TerraSAR-X (TSX) sensor during a full growth cycle of rice crops. The analysis shows good agreement for both datasets. The results of the proposed method emphasize the effectiveness of X-band PolSAR data for morphology-based growth stage determination of rice crops. View Full-Text
Keywords: rice growth; agriculture; crop morphology; Synthetic Aperture Radar (SAR); polarimetry; metamodels; Polynomial Chaos Expansion (PCE) rice growth; agriculture; crop morphology; Synthetic Aperture Radar (SAR); polarimetry; metamodels; Polynomial Chaos Expansion (PCE)
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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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Yuzugullu, O.; Marelli, S.; Erten, E.; Sudret, B.; Hajnsek, I. Determining Rice Growth Stage with X-Band SAR: A Metamodel Based Inversion. Remote Sens. 2017, 9, 460.

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