Joint-Pixel Inversion for Ground Phase and Forest Height Estimation Using Spaceborne Polarimetric SAR Interferometry.
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| Title: | Joint-Pixel Inversion for Ground Phase and Forest Height Estimation Using Spaceborne Polarimetric SAR Interferometry. |
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| Authors: | Huang, Zenghui1,2,3 (AUTHOR), Gao, Jingyu1,2,3 (AUTHOR), Lv, Xiaolei1,2,3 (AUTHOR), Li, Xiaoshuai1,2,3 (AUTHOR) |
| Source: | Remote Sensing. May2025, Vol. 17 Issue 10, p1726. 23p. |
| Subjects: | Covariance matrices, Pixels, Space-based radar, Interferometry, Problem solving, LIDAR, Synthetic aperture radar |
| Abstract: | Existing forest height estimation methods based on polarimetric interferometric synthetic aperture radar (PolInSAR) typically process each pixel independently, potentially introducing inconsistent estimates and additional decorrelation in the covariance matrix estimation. To address these limitations and effectively exploit the spatial context information, this paper proposes the first patch-based inversion method named joint pixel optimization inversion (JPO). By leveraging the smoothness and regularity of homogeneous pixels, a joint-pixel optimization problem is constructed, incorporating a first-order regularization on the ground phase. To solve the non-parallelizable problem of the alternating direction method of multipliers (ADMM), we devise a new parallelizable ADMM algorithm and prove its sublinear convergence. With the contextual information of neighboring pixels, JPO can provide more reliable forest height estimation and reduce the overestimation caused by additional decorrelation. The effectiveness of the proposed method is verified using spaceborne L-band repeat-pass SAOCOM acquisitions and LiDAR heights obtained from ICESat-2. Quantitative evaluations in forest height estimation show that the proposed method achieves a lower mean error (1.23 m) and RMSE (3.67 m) than the existing method (mean error: 3.09 m; RMSE: 4.70 m), demonstrating its improved reliability. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 185473553 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Joint-Pixel Inversion for Ground Phase and Forest Height Estimation Using Spaceborne Polarimetric SAR Interferometry. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Huang%2C+Zenghui%22">Huang, Zenghui</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gao%2C+Jingyu%22">Gao, Jingyu</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lv%2C+Xiaolei%22">Lv, Xiaolei</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Xiaoshuai%22">Li, Xiaoshuai</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. May2025, Vol. 17 Issue 10, p1726. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Covariance+matrices%22">Covariance matrices</searchLink><br /><searchLink fieldCode="DE" term="%22Pixels%22">Pixels</searchLink><br /><searchLink fieldCode="DE" term="%22Space-based+radar%22">Space-based radar</searchLink><br /><searchLink fieldCode="DE" term="%22Interferometry%22">Interferometry</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br /><searchLink fieldCode="DE" term="%22LIDAR%22">LIDAR</searchLink><br /><searchLink fieldCode="DE" term="%22Synthetic+aperture+radar%22">Synthetic aperture radar</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Existing forest height estimation methods based on polarimetric interferometric synthetic aperture radar (PolInSAR) typically process each pixel independently, potentially introducing inconsistent estimates and additional decorrelation in the covariance matrix estimation. To address these limitations and effectively exploit the spatial context information, this paper proposes the first patch-based inversion method named joint pixel optimization inversion (JPO). By leveraging the smoothness and regularity of homogeneous pixels, a joint-pixel optimization problem is constructed, incorporating a first-order regularization on the ground phase. To solve the non-parallelizable problem of the alternating direction method of multipliers (ADMM), we devise a new parallelizable ADMM algorithm and prove its sublinear convergence. With the contextual information of neighboring pixels, JPO can provide more reliable forest height estimation and reduce the overestimation caused by additional decorrelation. The effectiveness of the proposed method is verified using spaceborne L-band repeat-pass SAOCOM acquisitions and LiDAR heights obtained from ICESat-2. Quantitative evaluations in forest height estimation show that the proposed method achieves a lower mean error (1.23 m) and RMSE (3.67 m) than the existing method (mean error: 3.09 m; RMSE: 4.70 m), demonstrating its improved reliability. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=185473553 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs17101726 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 1726 Subjects: – SubjectFull: Covariance matrices Type: general – SubjectFull: Pixels Type: general – SubjectFull: Space-based radar Type: general – SubjectFull: Interferometry Type: general – SubjectFull: Problem solving Type: general – SubjectFull: LIDAR Type: general – SubjectFull: Synthetic aperture radar Type: general Titles: – TitleFull: Joint-Pixel Inversion for Ground Phase and Forest Height Estimation Using Spaceborne Polarimetric SAR Interferometry. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Huang, Zenghui – PersonEntity: Name: NameFull: Gao, Jingyu – PersonEntity: Name: NameFull: Lv, Xiaolei – PersonEntity: Name: NameFull: Li, Xiaoshuai IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 17 – Type: issue Value: 10 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
