Karakoram Highway (KKH) is frequently disrupted by geological hazards mainly landslides which pose a serious threat to its normal operation. Using documented inventory, optical imagery interpretation, and frequency-area statistics, the features of slope failure, the spatial distribution, and their link to numerous contributing factors have all been effectively explored along the KKH. An updated inventory for the area was recreated using the interferometric synthetic aperture radar (InSAR) persistent scatterer (PS) technology to further investigate millimetre-accurate measurements of slope deformation (V_slope). Utilizing the PS approach, Sentinel-1 data from Jan 2018 to Jan 2022 were processed by which we obtained a deformation rate (V_Slope) that varies between 0 and 364 mm/year. A total number of 234 landslides were cited from the literature and classified while 29 new potential landslides were detected and several pre-existing landslides were redefined by the InSAR approach, which was incorporated to generate an updated landslide susceptibility model with 86.6% of prediction precision in the area under curve method. As previous studies done by applying the InSAR technique incorporated a short span temporally and they missed some highly deforming zones like Budalas and Khanabad landslides, contain mean velocities > 50 mm/yr, which we studied individually in this work. In this study, a comprehensive application of the InSAR technique to assessing its performance in detecting and analysing landslides has been applied. The deformation velocity (V_slope) model shows high displacement in some regions, which needed to be further investigated by geoscientists, and the updated developed landslide inventory and susceptibility map can be used for land use planning and landslide mitigation strategies.

In various regions worldwide, people rely heavily on groundwater as a significant water source for daily usage. The resulting large-scale depletion of groundwater has triggered surface deformation in densely populated urban areas. This paper aims to employ Persistent Scattered Interferometry Synthetic Aperture Radar (PS-InSAR) techniques to monitor and quantify the land surface deformation (LSD), assess the relationships between LSD and groundwater levels (GWL), and provide insights for urban planning in Lahore, Pakistan, as the research area. A series of Sentinel-1 images from the ascending track between 2017 and 2020 were analyzed. Moreover, the Mann–Kendall (MK) test and coefficient of determination were computed to analyze the long-term trends and spatial relationships between GWL depletion and line of sight (LOS) displacement. Our findings reveal significant increases in land subsidence (LS) and GWL from 2017 to 2020, particularly in the city center of Lahore. Notably, the annual mean subsidence during this period rose from −27 mm/year to −106 mm/year, indicating an accelerating trend with an average subsidence of −20 mm/year. Furthermore, the MK test indicated a declining trend in GWL, averaging 0.49 m/year from 2003 to 2020, exacerbating LS. Regions with significant groundwater discharge are particularly susceptible to subsidence rates up to −100 mm. The LS variation was positively correlated with the GWL at a significant level (p < 0.05) and accounted for a high positive correlation at the center of the city, where the urban load was high. Overall, the adopted methodology effectively detects, maps, and monitors land surfaces vulnerable to subsidence, offering valuable insights into efficient sustainable urban planning, surface infrastructure design, and subsidence-induced hazard mitigation in large urban areas.

Northern Pakistan is a rugged mountainous area that is seismically active, high gradients, disintegrated lithology, and glaciers in the high peaks. District Ghizer lies among the most vulnerable areas and experience landslides every year due to different causative factors. This study has carried out to prepare a detailed landslide inventory and to develop a susceptibility model for the area. The most followed and probabilistic approach, Frequency Ratio (FR) model and a semi-qualitative Analytical Hierarchy Process (AHP) approach were applied to find the correlation between causative factors and mapped landslides. Persistent Scatterer Interferometry (PSI) Interferometric Synthetic Aperture Radar (InSAR) technique was applied to check deformation movement in the susceptible zones of extracted models, which showed the high Line of Sight (LOS) deformation velocity in high susceptible zones of both models. The extracted Landslide Susceptibility Index (LSI) models showed 82.82% and 73.43% of prediction accuracy for FR and AHP method calculated by Area Under Curve (AUC) of Receiver operating characteristic (ROC) method. The models revealed Slope, barrenness, and Geology are the main causative factors of landslide activities in the study area. Finally, both Landslide susceptibility index maps were classified into five susceptibility classes. As the study area is very prone to landslide disasters so these susceptibility models will be helpful to delineate hazardous zones for the medication of future landslides disasters in the area as well as it can be used as a tool in the planning strategies by decision-makers in development projects in the area.

Chitral valley lies in the eastern Hindu Kush range, one of the hotspot of landslide activities that leads to loss of lives and economy. Comprehensive landslide inventory and Landslide susceptibility provide the basic information to analyses and medicate the landslide activities which are not available for the area. Probabilistic and statistical methods have been using to develop susceptibility maps but limitations are countered to assess high accuracy. In this study Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique has been applied to estimate the slope deformation velocity (Vslope), which can be used to optimize the landslide susceptibility map for the study area. The frequency ratio and logistic regression models were applied for comparative assessment and to forecast the correlation between causative factors and landslide occurrence. Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) curve approach was used for accuracy comparison of both models which showed 75.45% and 85.61% accuracy for FR and LR respectively. LR method’s result was found superior and combined with the results of PS-InSAR to extract new Landslide Susceptibility Mapping (LSM) for the area which removed misclassifications in the results. This optimized susceptibility model will be helpful to mitigate the landslide disaster and provide support to authorities in the management of different development programs in the study area.

This study analyzed the land deformation associated with Mw 6.3 earthquake along Pasni coast, Pakistan. Post-earthquake widespread surface displacements were found using Sentinel-1 data. Pre, Co and Post-seismic images were used to investigate the deformation trends. Before the earthquake, 89.65% of Pasni land mass showed uplifting from 0.0 to 3.0 cm at 1.00 mm/day while 3.0 cm subsidence was noted in 86.36% of the land mass after the earthquake at 2.5 mm/day. However, two weeks after the earthquake, 72.9% Pasni land mass showed uplifting at an unprecedented rate of 3.3 mm/day. The maximum deformation along the Line Of Sight (LOS) direction in co-seismic time was about -4.0 cm. Azimuthal interferogram showed more complex displacement pattern with both negative and positive displacements between ±5.0 cm. Pasni is already facing many problems due to increased sea water intrusion under prevailing climatic changes and land deformation due to strong earthquakes.

InSAR-based deformation analysis and the geomorphic hypsometric integral (HI) technique are powerful tools for assessing the susceptibility and comparison of seismic sites to earthquakes. Therefore, this paper mainly focuses on surface deformation analysis associated with the Mw 5.0 earthquake (2019) in Mach and Quetta, Balochistan, Pakistan. Sentinel-1 IW data was used to perform PS-InSAR time series analysis. SRTM DEM of 30 m spatial resolution was utilized for the geomorphic Hypsometry Integral (HI) method. The obtained results of the Interferogram indicate the changes in velocity and vertical displacement during pre-seismic, co-seismic, and post-seismic activity. Integral values were calculated using Hypsometry curves delineating the future probability and comparison of vulnerable seismological sites in Mach, Quetta, Ghazaband, Chamman and surroundings of Balochistan region. The combined results of HI and PS-InSAR revealed that Mach and Quetta regions are in between two lines known as the mature stages. Class 1_moderate (0.35 ≤ HI ≤ 0.52); with an integral value of HI_Mach = 0.398 and HI_Quetta = 0.435 with a modest seismic forthcoming rate in future and susceptible to both erosion/uplifting with a vertical displacement rate more than existing ± 55 mm/year. Class 2_high (HI ˃ 0.53) with the younger and more tectonically active region surrounded by Chaman fault, which possesses a future susceptible tendency towards subsidence more than an existing velocity rate ~ 8 mm/year and Ghazaband fault towards uplifting more than 5–6 mm/year. No region of the study area was found at Monadnock: class 3_Low (HI ˂ 0.35) stabilized condition, all sites are unstable and tectonically active. Therefore, obtained results through combined PS-InSAR and HI techniques can be used for the identification of most vulnerable seismic sites and can ascertain future safe metropolitan planning.