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Remote Sens. 2017, 9(8), 819; doi:10.3390/rs9080819

A Modified Dual-Baseline PolInSAR Method for Forest Height Estimation

1
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
2
Institute for Computing Research (IUII), University of Alicante, E-03080 Alicante, Spain
*
Authors to whom correspondence should be addressed.
Academic Editors: Irena Hajnsek, Klaus Scipal, Pascale Dubois-Fernandez, Torbjorn Eltoft, Nicolas Baghdadi and Prasad S. Thenkabail
Received: 26 May 2017 / Revised: 21 July 2017 / Accepted: 4 August 2017 / Published: 9 August 2017
(This article belongs to the Special Issue Recent Advances in Polarimetric SAR Interferometry)
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Abstract

This paper investigates the potentials and limitations of a simple dual-baseline PolInSAR (DBPI) method for forest height inversion. This DBPI method follows the classical three-stage inversion method’s idea used in single baseline PolInSAR (SBPI) inversion, but it avoids the assumption of the smallest ground-to-volume amplitude ratio (GVR) by employing an additional baseline to constrain the inversion procedure. In this paper, we present for the first time an assessment of such a method on real PolInSAR data over boreal forest. Additionally, we propose an improvement on the original DBPI method by incorporating the sloped random volume over ground (S-RVoG) model in order to reduce the range terrain slope effect. Therefore, a digital elevation model (DEM) is needed to provide the slope information in the proposed method. Three scenes of P-band airborne PolInSAR data acquired by E-SAR and light detection and ranging (LIDAR) data available in the BioSAR2008 campaign are employed for testing purposes. The performance of the SBPI, DBPI, and modified DBPI methods is compared. The results show that the DBPI method extracts forest heights with an average root mean square error (RMSE) of 4.72 m against LIDAR heights for trees of 18 m height on average. It presents a significant improvement of forest height accuracy over the SBPI method (with a stand-level mean improvement of 42.86%). Concerning the modified DBPI method, it consistently improves the accuracy of forest height inversion over sloped areas. This improvement reaches a stand-level mean of 21.72% improvement (with a mean RMSE of 4.63 m) for slopes greater than 10°. View Full-Text
Keywords: forest height; polarimetric SAR interferometry (PolInSAR); dual-baseline; synthetic aperture radar (SAR); sloped random volume over ground (S-RVoG) model; P-band forest height; polarimetric SAR interferometry (PolInSAR); dual-baseline; synthetic aperture radar (SAR); sloped random volume over ground (S-RVoG) model; P-band
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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

Xie, Q.; Zhu, J.; Wang, C.; Fu, H.; Lopez-Sanchez, J.M.; Ballester-Berman, J.D. A Modified Dual-Baseline PolInSAR Method for Forest Height Estimation. Remote Sens. 2017, 9, 819.

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