View in EDS

Refined inversion of 3D surface subsidence in mining areas by integrating SBAS-InSAR and Log-logistic function.

Saved in:
Bibliographic Details
Title: Refined inversion of 3D surface subsidence in mining areas by integrating SBAS-InSAR and Log-logistic function.
Authors: Hong, Yang1 (AUTHOR), Chen, Peng1 (AUTHOR) chenpeng0123@gmail.com, Cao, Dongdong2 (AUTHOR), Yao, Yibin3,4 (AUTHOR), Liu, Hang1,5 (AUTHOR), Wu, Xiaolong1 (AUTHOR), Sun, Shizheng1 (AUTHOR)
Source: International Journal of Remote Sensing. Nov2025, Vol. 46 Issue 21, p7943-7969. 27p.
Subjects: Mining districts, Logistic functions (Mathematics), Deformations (Mechanics), Interferometry, Statistical models, Deformation of surfaces, Satellite positioning
Abstract: To address the poor convergence of the traditional Probability Integral Method (PIM) in predicting the boundaries of mining-induced subsidence – which often leads to substantial errors in three-dimensional (3D) displacement decomposition – this study proposes a refined 3D dynamic deformation monitoring method by integrating an improved PIM with Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR). First, Global Navigation Satellite System (GNSS) and SBAS-InSAR observations are jointly used to invert the parameters of the DPIM model, resulting in a more realistic GDPIM model that better reflects actual geological and mining conditions. Then, a Log-logistic temporal function is introduced to construct the GDPIM-Log model, enhancing the capacity to model the temporal evolution of subsidence. On this basis, leveraging the large-scale and high spatial resolution characteristics of InSAR data, a weighting strategy based on coherence, pixel distribution, and deformation gradient is applied to build a fused model – GDL-InSAR – for high-resolution 3D reconstruction of both vertical and horizontal displacements. The proposed method is validated using the Dahaize coal mine as a case study, with InSAR imagery and GNSS data acquired from July 2022 to June 2023. Results show that the average Root Mean Square Error (RMSE) along GNSS observation lines are 32.1 mm (vertical), 22.9 mm (east–west), and 34.2 mm (north–south), significantly outperforming the results of single-model inversion. The findings demonstrate that the proposed fusion method offers notable advantages in improving the accuracy of 3D subsidence monitoring in mining areas, enhancing model adaptability, and supporting practical engineering applications. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Remote Sensing is the property of Taylor & Francis Ltd 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
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 189083380
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Refined inversion of 3D surface subsidence in mining areas by integrating SBAS-InSAR and Log-logistic function.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hong%2C+Yang%22">Hong, Yang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Peng%22">Chen, Peng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chenpeng0123@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Cao%2C+Dongdong%22">Cao, Dongdong</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yao%2C+Yibin%22">Yao, Yibin</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Hang%22">Liu, Hang</searchLink><relatesTo>1,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Xiaolong%22">Wu, Xiaolong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Shizheng%22">Sun, Shizheng</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Remote+Sensing%22">International Journal of Remote Sensing</searchLink>. Nov2025, Vol. 46 Issue 21, p7943-7969. 27p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Mining+districts%22">Mining districts</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+functions+%28Mathematics%29%22">Logistic functions (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Deformations+%28Mechanics%29%22">Deformations (Mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Interferometry%22">Interferometry</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink><br /><searchLink fieldCode="DE" term="%22Deformation+of+surfaces%22">Deformation of surfaces</searchLink><br /><searchLink fieldCode="DE" term="%22Satellite+positioning%22">Satellite positioning</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: To address the poor convergence of the traditional Probability Integral Method (PIM) in predicting the boundaries of mining-induced subsidence – which often leads to substantial errors in three-dimensional (3D) displacement decomposition – this study proposes a refined 3D dynamic deformation monitoring method by integrating an improved PIM with Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR). First, Global Navigation Satellite System (GNSS) and SBAS-InSAR observations are jointly used to invert the parameters of the DPIM model, resulting in a more realistic GDPIM model that better reflects actual geological and mining conditions. Then, a Log-logistic temporal function is introduced to construct the GDPIM-Log model, enhancing the capacity to model the temporal evolution of subsidence. On this basis, leveraging the large-scale and high spatial resolution characteristics of InSAR data, a weighting strategy based on coherence, pixel distribution, and deformation gradient is applied to build a fused model – GDL-InSAR – for high-resolution 3D reconstruction of both vertical and horizontal displacements. The proposed method is validated using the Dahaize coal mine as a case study, with InSAR imagery and GNSS data acquired from July 2022 to June 2023. Results show that the average Root Mean Square Error (RMSE) along GNSS observation lines are 32.1 mm (vertical), 22.9 mm (east–west), and 34.2 mm (north–south), significantly outperforming the results of single-model inversion. The findings demonstrate that the proposed fusion method offers notable advantages in improving the accuracy of 3D subsidence monitoring in mining areas, enhancing model adaptability, and supporting practical engineering applications. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Remote Sensing is the property of Taylor & Francis Ltd 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=189083380
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/01431161.2025.2561134
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 27
        StartPage: 7943
    Subjects:
      – SubjectFull: Mining districts
        Type: general
      – SubjectFull: Logistic functions (Mathematics)
        Type: general
      – SubjectFull: Deformations (Mechanics)
        Type: general
      – SubjectFull: Interferometry
        Type: general
      – SubjectFull: Statistical models
        Type: general
      – SubjectFull: Deformation of surfaces
        Type: general
      – SubjectFull: Satellite positioning
        Type: general
    Titles:
      – TitleFull: Refined inversion of 3D surface subsidence in mining areas by integrating SBAS-InSAR and Log-logistic function.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hong, Yang
      – PersonEntity:
          Name:
            NameFull: Chen, Peng
      – PersonEntity:
          Name:
            NameFull: Cao, Dongdong
      – PersonEntity:
          Name:
            NameFull: Yao, Yibin
      – PersonEntity:
          Name:
            NameFull: Liu, Hang
      – PersonEntity:
          Name:
            NameFull: Wu, Xiaolong
      – PersonEntity:
          Name:
            NameFull: Sun, Shizheng
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 01431161
          Numbering:
            – Type: volume
              Value: 46
            – Type: issue
              Value: 21
          Titles:
            – TitleFull: International Journal of Remote Sensing
              Type: main
ResultId 1