Non-Linear PSInSAR Analysis of Surface Deformation Using Sentinel-1 Data: Evaluating the Effects of Urban Expansion

Surface deformation monitoring plays a crucial role in various fields, including geology, geodesy, and environmental studies. This study provides insights into the application of non-linear PSInSAR techniques for studying surface deformation associated with urban growth and groundwater pumping. A Persistent Scatterer InSAR (PSInSAR) analysis employing a time-segmented (non-linear) velocity model was applied to 119 Sentinel-1A ascending acquisitions spanning 10 February 2017 to 27 December 2020, yielding 38,594 persistent scatterers. The 33,238 scatterers were retained at a temporal coherence threshold of 0.70 and a mean density of 18.6 PS/km2 across the district, rising to 57 PS/km2 within the urban core, with annual mean line-of-sight (LOS) velocities measured for each calendar year. Temporal validation identifies a modest, origin-dependent forecasting benefit from segmentation in the urban core but no consistent advantage under contiguous block testing. Land use/land cover (LULC) was mapped from Landsat imagery for 2000, 2007, 2014, and 2020 using a random forest classifier in Google Earth Engine. LOS velocities span approximately +40 to −60 mm/yr over the mapped range, with the most negative values concentrated in the central urban core. Paired annual comparisons, accounting for spatial dependence and Holm adjustment across 15 tests, did not establish significant changes in the 0–2 km core. Significant contrasts occurred in two comparison annuli, but their physical origin remains unresolved. Land use classification maps for the years 2000, 2007, 2014, and 2020 show a significant expansion in built-up areas, coupled with a reduction in vegetation and, after adjustment for classification accuracy, in water bodies, which indicates the increasing pressure of urban growth on the environment. Lahore has witnessed a substantial increase in population due to urban migration, natural growth, and economic opportunities. Subsidence can lead to structural damage to buildings, infrastructure, and underground utilities. It is a serious concern in Lahore, particularly in areas where groundwater pumping is excessive.

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Publication Details

Journal
Remote Sensing
Published
2026-10-13
DOI
https://doi.org/10.3390/rs18203505
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Non-Linear PSInSAR Analysis of Surface Deformation Using Sentinel-1 Data: Evaluating the Effects of Urban Expansion

Maxim V. Kulemin, Dauren Zhexebay, A. Nedzved, Yuxiao Qin et al.
Remote Sensing
Synthetic Aperture Radar (SAR) Applications and Techniques
article

Non-Linear PSInSAR Analysis of Surface Deformation Using Sentinel-1 Data: Evaluating the Effects of Urban Expansion

Maxim V. Kulemin, Dauren Zhexebay, A. Nedzved, Yuxiao Qin, Alexei Belotserkovsky, Zeeshan Afzal, Danish Raza, Muhammad Ali, Margulan Ibraimov
article en

Abstract

Surface deformation monitoring plays a crucial role in various fields, including geology, geodesy, and environmental studies. This study provides insights into the application of non-linear PSInSAR techniques for studying surface deformation associated with urban growth and groundwater pumping. A Persistent Scatterer InSAR (PSInSAR) analysis employing a time-segmented (non-linear) velocity model was applied to 119 Sentinel-1A ascending acquisitions spanning 10 February 2017 to 27 December 2020, yielding 38,594 persistent scatterers. The 33,238 scatterers were retained at a temporal coherence threshold of 0.70 and a mean density of 18.6 PS/km2 across the district, rising to 57 PS/km2 within the urban core, with annual mean line-of-sight (LOS) velocities measured for each calendar year. Temporal validation identifies a modest, origin-dependent forecasting benefit from segmentation in the urban core but no consistent advantage under contiguous block testing. Land use/land cover (LULC) was mapped from Landsat imagery for 2000, 2007, 2014, and 2020 using a random forest classifier in Google Earth Engine. LOS velocities span approximately +40 to −60 mm/yr over the mapped range, with the most negative values concentrated in the central urban core. Paired annual comparisons, accounting for spatial dependence and Holm adjustment across 15 tests, did not establish significant changes in the 0–2 km core. Significant contrasts occurred in two comparison annuli, but their physical origin remains unresolved. Land use classification maps for the years 2000, 2007, 2014, and 2020 show a significant expansion in built-up areas, coupled with a reduction in vegetation and, after adjustment for classification accuracy, in water bodies, which indicates the increasing pressure of urban growth on the environment. Lahore has witnessed a substantial increase in population due to urban migration, natural growth, and economic opportunities. Subsidence can lead to structural damage to buildings, infrastructure, and underground utilities. It is a serious concern in Lahore, particularly in areas where groundwater pumping is excessive.

Remote SensingVol. 18(20)
National Academy of Sciences of Belarus (BY), Northwestern Polytechnical University (CN), Al-Farabi Kazakh National University (KZ), Harbin Institute of Technology (CN), Belarusian State University (BY), Wuhan University (CN), United Institute of Informatics Problems (BY), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 18%
Synthetic Aperture Radar (SAR) Applications and Techniques
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