Treating Tropospheric Phase Delay in Large-scale Sentinel-1 Stacks to Analyze Land Subsidence

authored by: Mahmud Haghshenas Haghighi, Mahdi Motagh
Abstract: Variations in the tropospheric phase delay pose a primary challenge to achieving precise displacement measurements in Interferometric Synthetic Aperture Radar (InSAR) analysis. This study presents a cluster-based empirical tropospheric phase correction approach to analyze land subsidence rates from large-scale Sentinel‑1 data stacks. Our method identifies the optimum number of clusters in individual interferograms for K‑means clustering, and segments extensive interferograms into areas with consistent tropospheric phase delay behaviors. It then performs tropospheric phase correction based on empirical topography-phase correlation, addressing stratified and broad-scale tropospheric phase delays. Applied to a six-year data stack along a 1000-km track in Iran, we demonstrate that this approach enhances interferogram quality by reducing the standard deviation by 50% and lowering the semivariance of the interferograms to 20 cm² at distances up to 800 km in 97% of the interferograms. Additionally, the corrected time series of deformation shows a 40% reduction in the root mean square of residuals at the most severely deformed points. By analyzing the corrected interferograms, we show that our method improves the efficiency of country-scale InSAR surveys to detect and quantify present-day land subsidence in Iran, which is essential for groundwater management and sustainable water resource planning.
Organisation(s): Institute of Photogrammetry and GeoInformation (IPI)
External Organisation(s): Helmholtz Centre Potsdam - German Research Centre for Geosciences (GFZ)
Type: Article
Journal: PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science
Volume: 92
Pages: 593-607
No. of pages: 15
ISSN: 2512-2789
Publication date: 10.2024
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Geography, Planning and Development, Instrumentation, Earth and Planetary Sciences (miscellaneous)
Electronic version(s): https://doi.org/10.1007/s41064-024-00304-z (Access: Open)

BibTeX

@article{60763b74521b4ab9958fe7e3c7f4657e,
title = "Treating Tropospheric Phase Delay in Large-scale Sentinel-1 Stacks to Analyze Land Subsidence",
abstract = "Variations in the tropospheric phase delay pose a primary challenge to achieving precise displacement measurements in Interferometric Synthetic Aperture Radar (InSAR) analysis. This study presents a cluster-based empirical tropospheric phase correction approach to analyze land subsidence rates from large-scale Sentinel‑1 data stacks. Our method identifies the optimum number of clusters in individual interferograms for K‑means clustering, and segments extensive interferograms into areas with consistent tropospheric phase delay behaviors. It then performs tropospheric phase correction based on empirical topography-phase correlation, addressing stratified and broad-scale tropospheric phase delays. Applied to a six-year data stack along a 1000-km track in Iran, we demonstrate that this approach enhances interferogram quality by reducing the standard deviation by 50% and lowering the semivariance of the interferograms to 20 cm2 at distances up to 800 km in 97% of the interferograms. Additionally, the corrected time series of deformation shows a 40% reduction in the root mean square of residuals at the most severely deformed points. By analyzing the corrected interferograms, we show that our method improves the efficiency of country-scale InSAR surveys to detect and quantify present-day land subsidence in Iran, which is essential for groundwater management and sustainable water resource planning.",
keywords = "InSAR, Land Subsidence, Sentinel‑1, Tropospheric Correction",
author = "{Haghshenas Haghighi}, Mahmud and Mahdi Motagh",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",
year = "2024",
month = oct,
doi = "10.1007/s41064-024-00304-z",
language = "English",
volume = "92",
pages = "593--607",
journal = "PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science",
issn = "2512-2789",
publisher = "Springer International Publishing AG",
number = "5",
}