Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China

Spaceborne polarimetric synthetic aperture radar interferometry (PolInSAR) has the potential to deal with large-scale forest height inversion. However, the inversion is influenced by strong temporal decorrelation interference resulting from a large temporal baseline. Additionally, the forest canopy...

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Autores principales:	Yu Mao, Opelele Omeno Michel, Ying Yu, Wenyi Fan, Ao Sui, Zhihui Liu, Guoming Wu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	forest height synthetic aperture radar (SAR) interferometry random volume over ground (RVoG) model three-stage inversion method Science Q
Acceso en línea:	https://doaj.org/article/a5b7d89a64d84675bb13e33d3ee28be1
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spelling	oai:doaj.org-article:a5b7d89a64d84675bb13e33d3ee28be12021-11-11T18:53:31ZRetrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China10.3390/rs132143062072-4292https://doaj.org/article/a5b7d89a64d84675bb13e33d3ee28be12021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4306https://doaj.org/toc/2072-4292Spaceborne polarimetric synthetic aperture radar interferometry (PolInSAR) has the potential to deal with large-scale forest height inversion. However, the inversion is influenced by strong temporal decorrelation interference resulting from a large temporal baseline. Additionally, the forest canopy induces phase errors, while the smaller vertical wavenumber (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>k</mi><mi>z</mi></msub></mrow></semantics></math></inline-formula>) enhances the sensitivity of the inversion to temporal decorrelation, which limits the efficiency in forest height inversion. This research is based on the random volume over ground (RVoG) model and follows the assumptions of the three-stage inversion method, to quantify the impact of repeat-pass spaceborne PolInSAR temporal decorrelation on the relative error of retrieval height, and develop a semi-empirical improved inversion model, using ground data to eliminate the interference of coherence and phase error caused by temporal decorrelation. Forest height inversion for temperate forest in northern China was conducted using repeat-pass spaceborne L-band ALOS2 PALSAR data, and was further verified using ground measurement data. The correction of temporal decorrelation using the improved model provided robust inversion for mixed conifer-broad forest height retrieval as it addressed the over-sensitivity to temporal decorrelation resulting from the inappropriate <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>k</mi><mi>z</mi></msub></mrow></semantics></math></inline-formula> value. The method performed height inversion using interferometric data with temporal baselines ranging from 14 to 70 days and vertical wavenumbers ranging from 0.015 to 0.021 rad/m. The R<sup>2</sup> and RMSE reached 0.8126 and 2.3125 m, respectively.Yu MaoOpelele Omeno MichelYing YuWenyi FanAo SuiZhihui LiuGuoming WuMDPI AGarticleforest heightsynthetic aperture radar (SAR)interferometryrandom volume over ground (RVoG) modelthree-stage inversion methodScienceQENRemote Sensing, Vol 13, Iss 4306, p 4306 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	forest height synthetic aperture radar (SAR) interferometry random volume over ground (RVoG) model three-stage inversion method Science Q
spellingShingle	forest height synthetic aperture radar (SAR) interferometry random volume over ground (RVoG) model three-stage inversion method Science Q Yu Mao Opelele Omeno Michel Ying Yu Wenyi Fan Ao Sui Zhihui Liu Guoming Wu Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China
description	Spaceborne polarimetric synthetic aperture radar interferometry (PolInSAR) has the potential to deal with large-scale forest height inversion. However, the inversion is influenced by strong temporal decorrelation interference resulting from a large temporal baseline. Additionally, the forest canopy induces phase errors, while the smaller vertical wavenumber (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>k</mi><mi>z</mi></msub></mrow></semantics></math></inline-formula>) enhances the sensitivity of the inversion to temporal decorrelation, which limits the efficiency in forest height inversion. This research is based on the random volume over ground (RVoG) model and follows the assumptions of the three-stage inversion method, to quantify the impact of repeat-pass spaceborne PolInSAR temporal decorrelation on the relative error of retrieval height, and develop a semi-empirical improved inversion model, using ground data to eliminate the interference of coherence and phase error caused by temporal decorrelation. Forest height inversion for temperate forest in northern China was conducted using repeat-pass spaceborne L-band ALOS2 PALSAR data, and was further verified using ground measurement data. The correction of temporal decorrelation using the improved model provided robust inversion for mixed conifer-broad forest height retrieval as it addressed the over-sensitivity to temporal decorrelation resulting from the inappropriate <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>k</mi><mi>z</mi></msub></mrow></semantics></math></inline-formula> value. The method performed height inversion using interferometric data with temporal baselines ranging from 14 to 70 days and vertical wavenumbers ranging from 0.015 to 0.021 rad/m. The R<sup>2</sup> and RMSE reached 0.8126 and 2.3125 m, respectively.
format	article
author	Yu Mao Opelele Omeno Michel Ying Yu Wenyi Fan Ao Sui Zhihui Liu Guoming Wu
author_facet	Yu Mao Opelele Omeno Michel Ying Yu Wenyi Fan Ao Sui Zhihui Liu Guoming Wu
author_sort	Yu Mao
title	Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China
title_short	Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China
title_full	Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China
title_fullStr	Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China
title_full_unstemmed	Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China
title_sort	retrieval of boreal forest heights using an improved random volume over ground (rvog) model based on repeat-pass spaceborne polarimetric sar interferometry: the case study of saihanba, china
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a5b7d89a64d84675bb13e33d3ee28be1
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Retrieval of Boreal Forest Heights Using an Improved Random Volume over Ground (RVoG) Model Based on Repeat-Pass Spaceborne Polarimetric SAR Interferometry: The Case Study of Saihanba, China

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