Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear Model
Accurate atmospheric correction is critical for improving the reliability of InSAR deformation monitoring in mountainous area, such as southeastern edge of the Tibetan Plateau, where rugged topography and complex atmospheric conditions introduce significant tropospheric delays. Traditional correctio...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/11062326/ |
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| author | Menghua Li Dongxu Huang Mengshi Yang Weitao Tian Cheng Huang Bo-Hui Tang |
| author_facet | Menghua Li Dongxu Huang Mengshi Yang Weitao Tian Cheng Huang Bo-Hui Tang |
| author_sort | Menghua Li |
| collection | DOAJ |
| description | Accurate atmospheric correction is critical for improving the reliability of InSAR deformation monitoring in mountainous area, such as southeastern edge of the Tibetan Plateau, where rugged topography and complex atmospheric conditions introduce significant tropospheric delays. Traditional correction methods, including global linear models (LMs), regular-window segmented linear model (RSLMs), and numerical weather models such as ERA-5 and Generic Atmospheric Correction Online Service (GACOS), often fail to address the spatial heterogeneity of atmospheric signals in such terrains, leaving residual artifacts that obscure surface deformation measurements. To overcome these limitations, this study proposes a watershed-segmented linear model (WSLM) that incorporates vertical atmospheric stratification and lateral watershed boundaries to effectively capture localized atmospheric variability. The performance of WSLM was evaluated using both simulated datasets and real Sentinel-1 data from the Deqin section of the Lancang River and compared with corrections provided by LM, RSLM, GACOS, and ERA-5 corrections. The results show that WSLM effectively reduces atmospheric artifacts, mitigates vertical stratification delays, and improves the recovery of realistic deformation signals. Compared to existing methods, it achieves lower residual phase standard deviations—reducing them by up to 75.78% —weakens phase-elevation correlations, and enhances time-series displacement accuracy. While uncertainties remain in determining the optimal weighting factors and segmentation thresholds, WSLM effectively reduces atmospheric errors and provides valuable insights for deformation monitoring in complex mountainous environments. |
| format | Article |
| id | doaj-art-e73a5a112f7f4bc6bb72d4b7f723f430 |
| institution | Matheson Library |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-e73a5a112f7f4bc6bb72d4b7f723f4302025-07-17T23:00:26ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-0118168681687810.1109/JSTARS.2025.358482111062326Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear ModelMenghua Li0https://orcid.org/0000-0002-8027-4866Dongxu Huang1Mengshi Yang2https://orcid.org/0000-0003-1449-3494Weitao Tian3Cheng Huang4Bo-Hui Tang5https://orcid.org/0000-0002-1918-5346Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, ChinaFaculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, ChinaSchool of Earth Science, Yunnan University, Kunming, ChinaFaculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, ChinaFaculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, ChinaFaculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, ChinaAccurate atmospheric correction is critical for improving the reliability of InSAR deformation monitoring in mountainous area, such as southeastern edge of the Tibetan Plateau, where rugged topography and complex atmospheric conditions introduce significant tropospheric delays. Traditional correction methods, including global linear models (LMs), regular-window segmented linear model (RSLMs), and numerical weather models such as ERA-5 and Generic Atmospheric Correction Online Service (GACOS), often fail to address the spatial heterogeneity of atmospheric signals in such terrains, leaving residual artifacts that obscure surface deformation measurements. To overcome these limitations, this study proposes a watershed-segmented linear model (WSLM) that incorporates vertical atmospheric stratification and lateral watershed boundaries to effectively capture localized atmospheric variability. The performance of WSLM was evaluated using both simulated datasets and real Sentinel-1 data from the Deqin section of the Lancang River and compared with corrections provided by LM, RSLM, GACOS, and ERA-5 corrections. The results show that WSLM effectively reduces atmospheric artifacts, mitigates vertical stratification delays, and improves the recovery of realistic deformation signals. Compared to existing methods, it achieves lower residual phase standard deviations—reducing them by up to 75.78% —weakens phase-elevation correlations, and enhances time-series displacement accuracy. While uncertainties remain in determining the optimal weighting factors and segmentation thresholds, WSLM effectively reduces atmospheric errors and provides valuable insights for deformation monitoring in complex mountainous environments.https://ieeexplore.ieee.org/document/11062326/Interferometric synthetic aperture radar (InSAR)time-series InSARatmospheric delay correctionwatershed-segmented linear model |
| spellingShingle | Menghua Li Dongxu Huang Mengshi Yang Weitao Tian Cheng Huang Bo-Hui Tang Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear Model IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Interferometric synthetic aperture radar (InSAR) time-series InSAR atmospheric delay correction watershed-segmented linear model |
| title | Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear Model |
| title_full | Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear Model |
| title_fullStr | Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear Model |
| title_full_unstemmed | Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear Model |
| title_short | Improving InSAR Tropospheric Delay Correction in Deep Canyon Regions With a DEM Watershed-Based Segmented Linear Model |
| title_sort | improving insar tropospheric delay correction in deep canyon regions with a dem watershed based segmented linear model |
| topic | Interferometric synthetic aperture radar (InSAR) time-series InSAR atmospheric delay correction watershed-segmented linear model |
| url | https://ieeexplore.ieee.org/document/11062326/ |
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