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Groundwater dynamics caused by extraction and recharge are one of the primary causes of subsidence in the urban environment. Lahore is the second largest metropolitan city in Pakistan. The rapid expansion of this urban area due to high population density has increased the demand for groundwater to meet commercial and household needs. Land subsidence due to inadequate groundwater extraction has long been a concern in Lahore. This paper aims to present the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technique for monitoring the recent land subsidence in Lahore, based on the Sentinel-1 data obtained from January 2020 to December 2021. PS-InSAR techniques are very efficient and cost-effective, determining land subsidence and providing useful results. Areas of high groundwater discharge are prone to high subsidence of −110 mm, while the surroundings show an uplifting of +21 mm during the study period. The PS-InSAR study exposes the subsidence area in detail, particularly when the subsoil is characterized by alluvial and clay deposits and large building structures. This type of observation is quite satisfactory and similar to ground-based surface deformation pertinent to a high subsidence rate. Results will enable more effective urban planning, land infrastructure building, and risk assessment related to subsidence. [ABSTRACT FROM AUTHOR]

Landslides are the most catastrophic geological hazard in hilly areas. The present work intends to identify landslide susceptibility along Karakorum Highway (KKH) in Northern Pakistan, using landslide susceptibility mapping (LSM). To compare and predict the connection between causative factors and landslides, the random forest (RF), extreme gradient boosting (XGBoost), k nearest neighbor (KNN) and naive Bayes (NB) models were used in this research. Interferometric synthetic aperture radar persistent scatterer interferometry (PS-InSAR) technology was used to explore the displacement movement of retrieved models. Initially, 332 landslide areas alongside the Karakorum Highway were found to generate the landslide inventory map using various data. The landslides were categorized into two sections for validation and training, of 30% and 70%. For susceptibility mapping, thirteen landslide-condition factors were created. The area under curve (AUC) of the receiver operating characteristic (ROC) curve technique was utilized for accuracy comparison, yielding 83.08, 82.15, 80.31, and 72.92% accuracy for RF, XGBoost, KNN, and NB, respectively. The PS-InSAR technique demonstrated a high deformation velocity along the line of sight (LOS) in model-sensitive areas. The PS-InSAR technique was used to evaluate the slope deformation velocity, which can be used to improve the LSM for the research region. The RF technique yielded superior findings, integrating with the PS-InSAR outcomes to provide the region with a new landslide susceptibility map. The enhanced model will help mitigate landslide catastrophes, and the outcomes may help ensure the roadway's safe functioning in the study region. [ABSTRACT FROM AUTHOR]