Land Subsidence Monitoring Method in Regions of Variable Radar Reflection Characteristics by Integrating PS-InSAR and SBAS-InSAR Techniques Article Swipe
Peng Zhang
,
Zihao Guo
,
Shuangfeng Guo
,
Jin Xia
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/rs14143265
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/rs14143265
In the InSAR solution, the uneven distribution of permanent scatterer candidates (PSCs) or slowly decoherent filtering phase (SDFP) pixel density in a region of variable radar reflection feature can cause local low accuracy in single interferometry. PSCs with higher-order coherence in Permanent Scatter InSAR (PS-InSAR) are generally distributed in those point targets of urban built-up areas, and SDFP pixels in Small Baseline Subset InSAR (SBAS-InSAR) are generally distributed in those distributed targets of countryside vegetation areas. According to the respective reliability of PS-InSAR and SBAS-InSAR for different radar reflection features, a new land subsidence monitoring method is proposed, which combines PS-SBAS InSAR by data fusion of different interferometry in different radar reflection regions. Density-based spatial clustering of applications with noise (DBSCAN) clustering analysis is carried out on the density of PSCs with higher-order coherence in PS-InSAR processing to zone the region of variable radar reflection features for acquiring the boundary of data fusion. The vector monitoring data of PS-InSAR is retained in the dense region of PSCs with higher-order coherence, and the vector monitoring data of SBAS-InSAR is used in the sparse region of PSCs with higher-order coherence. The vertical displacements from PS-InSAR and SBAS-InSAR are integrated to obtain the optimal land subsidence. The verification case of 38 SAR images acquired by the Sentinel-1A in Suzhou city indicates that the proposed method can automatically choose a matched interferometry technique according to the variability of radar reflection features in the region and improve the accuracy of using a single interferometry method. The integrated method of the combined field is more representative of overall subsidence characteristics than the PS-InSAR-only or SBAS-InSAR-only results, and it is better suited for the assessment of the impact of land subsidence over the study area. The research results of this paper can provide a useful comprehensive reference for city planning and help decrease land subsidence in Suzhou.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs14143265
- https://www.mdpi.com/2072-4292/14/14/3265/pdf?version=1657119898
- OA Status
- gold
- Cited By
- 66
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4286629040
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- OpenAlex ID
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https://openalex.org/W4286629040Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs14143265Digital Object Identifier
- Title
-
Land Subsidence Monitoring Method in Regions of Variable Radar Reflection Characteristics by Integrating PS-InSAR and SBAS-InSAR TechniquesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-07-06Full publication date if available
- Authors
-
Peng Zhang, Zihao Guo, Shuangfeng Guo, Jin XiaList of authors in order
- Landing page
-
https://doi.org/10.3390/rs14143265Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/14/14/3265/pdf?version=1657119898Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2072-4292/14/14/3265/pdf?version=1657119898Direct OA link when available
- Concepts
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Interferometric synthetic aperture radar, Remote sensing, Radar, Coherence (philosophical gambling strategy), Interferometry, GNSS augmentation, Geology, Geodesy, Computer science, Synthetic aperture radar, Global Positioning System, GNSS applications, Optics, Telecommunications, Mathematics, Physics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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66Total citation count in OpenAlex
- Citations by year (recent)
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2025: 33, 2024: 14, 2023: 18, 2012: 1Per-year citation counts (last 5 years)
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40Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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