Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes

Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation,...
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Gespeichert in:

Autor*in:	Chang Liu [verfasserIn] Qi Zhang [verfasserIn] Linlin Ge [verfasserIn] Samad M. E. Sepasgozar [verfasserIn] Ziheng Sheng [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	forest height Pol-InSAR repeat-pass spaceborne temporal decorrelation dielectric property

Übergeordnetes Werk:	In: Remote Sensing - MDPI AG, 2009, 15(2023), 7, p 1877
Übergeordnetes Werk:	volume:15 ; year:2023 ; number:7, p 1877

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/rs15071877

Katalog-ID:	DOAJ089346300

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520			\|a Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation, which can cause a forest height overestimation error. However, most forest height estimation studies have not considered the change in dielectric property as a factor that may cause temporal decorrelation with a long temporal baseline. Therefore, it is necessary to propose a new method that considers dielectric fluctuations and random motions of scattering elements to compensate for the temporal decorrelation effect. The lack of ground truth for forest canopy also needs a solution. Unsupervised methods could be a solution because they do not require the use of true values of tree heights as the ground truth to calculate their estimation accuracies. This paper aims to present an unsupervised forest height estimation method called Dielectric Fluctuation and Random Motion over Ground (DF-RMoG) to improve accuracy by considering the dielectric fluctuations and random motions. Its performance is investigated using Advanced Land Observing Satellite (ALOS)-1 Pol-InSAR data acquired over a German forest site with temporal intervals of 46 and 92 days. The authors analyze the relationship between forest height and different parameters with DF-RMoG and conventional models. Compared with conventional models, the proposed DF-RMoG model significantly reduces the overestimation error due to temporal decorrelation in forest height estimation according to its lowest average forest height.
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spelling	10.3390/rs15071877 doi (DE-627)DOAJ089346300 (DE-599)DOAJ13dd2d2c833142fb90b790ebe7e803c2 DE-627 ger DE-627 rakwb eng Chang Liu verfasserin aut Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation, which can cause a forest height overestimation error. However, most forest height estimation studies have not considered the change in dielectric property as a factor that may cause temporal decorrelation with a long temporal baseline. Therefore, it is necessary to propose a new method that considers dielectric fluctuations and random motions of scattering elements to compensate for the temporal decorrelation effect. The lack of ground truth for forest canopy also needs a solution. Unsupervised methods could be a solution because they do not require the use of true values of tree heights as the ground truth to calculate their estimation accuracies. This paper aims to present an unsupervised forest height estimation method called Dielectric Fluctuation and Random Motion over Ground (DF-RMoG) to improve accuracy by considering the dielectric fluctuations and random motions. Its performance is investigated using Advanced Land Observing Satellite (ALOS)-1 Pol-InSAR data acquired over a German forest site with temporal intervals of 46 and 92 days. The authors analyze the relationship between forest height and different parameters with DF-RMoG and conventional models. Compared with conventional models, the proposed DF-RMoG model significantly reduces the overestimation error due to temporal decorrelation in forest height estimation according to its lowest average forest height. forest height Pol-InSAR repeat-pass spaceborne temporal decorrelation dielectric property Science Q Qi Zhang verfasserin aut Linlin Ge verfasserin aut Samad M. E. Sepasgozar verfasserin aut Ziheng Sheng verfasserin aut In Remote Sensing MDPI AG, 2009 15(2023), 7, p 1877 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:15 year:2023 number:7, p 1877 https://doi.org/10.3390/rs15071877 kostenfrei https://doaj.org/article/13dd2d2c833142fb90b790ebe7e803c2 kostenfrei https://www.mdpi.com/2072-4292/15/7/1877 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 15 2023 7, p 1877
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author	Chang Liu
spellingShingle	Chang Liu misc forest height misc Pol-InSAR misc repeat-pass misc spaceborne misc temporal decorrelation misc dielectric property misc Science misc Q Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes
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topic_title	Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes forest height Pol-InSAR repeat-pass spaceborne temporal decorrelation dielectric property
topic	misc forest height misc Pol-InSAR misc repeat-pass misc spaceborne misc temporal decorrelation misc dielectric property misc Science misc Q
topic_unstemmed	misc forest height misc Pol-InSAR misc repeat-pass misc spaceborne misc temporal decorrelation misc dielectric property misc Science misc Q
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title	Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes
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title_full	Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes
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title_sort	dielectric fluctuation and random motion over ground model (df-rmog): an unsupervised three-stage method of forest height estimation considering dielectric property changes
title_auth	Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes
abstract	Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation, which can cause a forest height overestimation error. However, most forest height estimation studies have not considered the change in dielectric property as a factor that may cause temporal decorrelation with a long temporal baseline. Therefore, it is necessary to propose a new method that considers dielectric fluctuations and random motions of scattering elements to compensate for the temporal decorrelation effect. The lack of ground truth for forest canopy also needs a solution. Unsupervised methods could be a solution because they do not require the use of true values of tree heights as the ground truth to calculate their estimation accuracies. This paper aims to present an unsupervised forest height estimation method called Dielectric Fluctuation and Random Motion over Ground (DF-RMoG) to improve accuracy by considering the dielectric fluctuations and random motions. Its performance is investigated using Advanced Land Observing Satellite (ALOS)-1 Pol-InSAR data acquired over a German forest site with temporal intervals of 46 and 92 days. The authors analyze the relationship between forest height and different parameters with DF-RMoG and conventional models. Compared with conventional models, the proposed DF-RMoG model significantly reduces the overestimation error due to temporal decorrelation in forest height estimation according to its lowest average forest height.
abstractGer	Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation, which can cause a forest height overestimation error. However, most forest height estimation studies have not considered the change in dielectric property as a factor that may cause temporal decorrelation with a long temporal baseline. Therefore, it is necessary to propose a new method that considers dielectric fluctuations and random motions of scattering elements to compensate for the temporal decorrelation effect. The lack of ground truth for forest canopy also needs a solution. Unsupervised methods could be a solution because they do not require the use of true values of tree heights as the ground truth to calculate their estimation accuracies. This paper aims to present an unsupervised forest height estimation method called Dielectric Fluctuation and Random Motion over Ground (DF-RMoG) to improve accuracy by considering the dielectric fluctuations and random motions. Its performance is investigated using Advanced Land Observing Satellite (ALOS)-1 Pol-InSAR data acquired over a German forest site with temporal intervals of 46 and 92 days. The authors analyze the relationship between forest height and different parameters with DF-RMoG and conventional models. Compared with conventional models, the proposed DF-RMoG model significantly reduces the overestimation error due to temporal decorrelation in forest height estimation according to its lowest average forest height.
abstract_unstemmed	Polarimetric Synthetic Aperture Radar Interferometry (Pol-InSAR) based forest height estimation for ecosystem monitoring and management has been developing rapidly in recent years. Spaceborne Pol-InSAR systems with long temporal baselines of several days always lead to severe temporal decorrelation, which can cause a forest height overestimation error. However, most forest height estimation studies have not considered the change in dielectric property as a factor that may cause temporal decorrelation with a long temporal baseline. Therefore, it is necessary to propose a new method that considers dielectric fluctuations and random motions of scattering elements to compensate for the temporal decorrelation effect. The lack of ground truth for forest canopy also needs a solution. Unsupervised methods could be a solution because they do not require the use of true values of tree heights as the ground truth to calculate their estimation accuracies. This paper aims to present an unsupervised forest height estimation method called Dielectric Fluctuation and Random Motion over Ground (DF-RMoG) to improve accuracy by considering the dielectric fluctuations and random motions. Its performance is investigated using Advanced Land Observing Satellite (ALOS)-1 Pol-InSAR data acquired over a German forest site with temporal intervals of 46 and 92 days. The authors analyze the relationship between forest height and different parameters with DF-RMoG and conventional models. Compared with conventional models, the proposed DF-RMoG model significantly reduces the overestimation error due to temporal decorrelation in forest height estimation according to its lowest average forest height.
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title_short	Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes
url	https://doi.org/10.3390/rs15071877 https://doaj.org/article/13dd2d2c833142fb90b790ebe7e803c2 https://www.mdpi.com/2072-4292/15/7/1877 https://doaj.org/toc/2072-4292
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up_date	2024-07-03T22:36:07.245Z
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Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes

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