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- MakaleAçık Erişim2026Severity-Based Mapping of Land-Subsidence Hazard Zones and Critical Hotspots Using SBAS-InSAR and Spatial Statistics: The Konya Metropolitan Area, Turkey
Yalvac, Sefa; Bjelotomić Oršulić, Olga
Land subsidence induced by excessive groundwater withdrawal has become one of the most significant geohazards affecting the Konya Closed Basin, Turkey. Although previous studies have successfully monitored ground deformation using geodetic and remote sensing techniques, limited attention has been devoted to transforming deformation measurements into quantitative, spatially classified hazard information. This study presents a severity-based framework for delineating land-subsidence hazard zones and critical hotspots in the Konya metropolitan area by integrating SBAS-InSAR observations and spatial statistical analyses. A total of 82 Sentinel-1 SAR acquisitions (41 ascending and 41 descending images) acquired between January 2023 and May 2026 were processed using the Small Baseline Subset (SBAS) technique. Ascending and descending line-of-sight deformation measurements were combined to derive vertical deformation rates, which were integrated with spatial statistical indicators and a composite severity index to quantify deformation clustering and classify subsidence severity. Hazard zones and critical hotspot areas were delineated through severity-based classification and spatial connectivity analyses. The results reveal a continuous north–south-oriented subsidence deformation belt extending across the eastern Konya. Maximum vertical subsidence rates exceeded 230 mm/yr, while spatial statistical analyses confirmed strongly clustered and statistically significant deformation patterns. Severity-based hazard zonation identified four hazard classes and a continuous high-hazard corridor. Clustering analysis further identified a dominant hotspot belt covering approximately 160 km2, with mean subsidence rates of approximately 142 mm/yr. A sensitivity analysis of the composite severity index weighting scheme, the spatial statistical neighborhood distance, the DBSCAN clustering parameters, and the number of Jenks severity classes confirmed that the resulting hazard zones and critical hotspot belt are robust to reasonable parameter variations. The findings demonstrate that land subsidence in Konya is organized as a spatially continuous regional-scale deformation system rather than a collection of isolated subsidence centers. The proposed framework transforms InSAR-derived deformation measurements into quantitative, decision-support hazard information and provides a transferable methodology for land-subsidence hazard assessment in groundwater-stressed urban environments.
- MakaleAçık Erişim2026Land Subsidence Susceptibility Mapping in Semi-Arid Regions Using PS-InSAR and Tree-Based Ensemble Machine Learning: A Case Study From Çumra, Türkiye
Bilgilioğlu, Burhan Baha
Land subsidence is an increasing environmental hazard in semi-arid agricultural basins where intensive groundwater abstraction, compressible geological units, and expanding land-use pressures interact. This study presents a PS-InSAR and machine-learning-based framework for land subsidence susceptibility mapping in the Çumra District of the Konya Closed Basin, Türkiye. A time-series PS-InSAR analysis was conducted using 172 Sentinel-1A ascending images acquired between 2018 and 2023, and 11,718 high-confidence subsidence points were extracted as the inventory dataset. Fourteen conditioning factors representing topographic, hydrogeological, lithological, environmental, and anthropogenic controls were integrated with eight tree-based ensemble models optimized using Optuna. Random Forest achieved the highest overall performance, with an accuracy of 0.9745, precision of 0.9562, recall of 0.9945, F1 score of 0.9750, and Cohen's Kappa of 0.9490, followed by Extremely Randomized Trees and XGBoost. Class-specific validation also confirmed the reliability of Random Forest in delineating the Very High Susceptibility class. Variable importance analysis identified land use, proximity to settlements, well density, and groundwater level change as the dominant predictors, emphasizing the role of groundwater-related anthropogenic pressure in subsidence development. The resulting susceptibility maps provide a spatial decision-support basis for groundwater management, land use planning, and subsidence risk mitigation.
- MakaleYalnız künye2023Excessive groundwater withdrawal and resultant land subsidence in the Küçük Menderes River Basin, Turkey as estimated from InSAR-SBAS and GNSS measurements
Yalvaç, Sefa; Alemdağ, Selçuk; Zeybek, Halil İbrahim; Yalvaç, Murat
Küçük Menderes River Basin (KMRB) is located in the western part of Turkey in the city of İzmir. The basin hosts about half a million people and 90% of the population makes their living from farming and animal husbandry. Most of the water needs for agricultural irrigation, animal husbandry, and drinking are met from groundwater resources in the basin. Since the water pumped from the aquifers cannot be naturally recharged by surface waters and precipitation, the groundwater level is rapidly receding and a decrease of up to 150 meters has been observed in the historical groundwater level time series since the 1990s. For this reason, land subsidence occurred in the basin and as a result of this, crustal surface cracks have formed and infrastructure and superstructure facilities have been endangered. To prevent loss of life and property that may occur in the future, it has become necessary to estimate the magnitude and the expansion zone of the land subsidence by carrying out geodetic monitoring studies in the region. In this study, the analyzes performed by Interferometric Synthetic Aperture Radar-Small Baseline Subset (InSAR-SBAS) and Global Navigation Satellite System (GNSS) methods to monitor land subsidence in the KMRB are presented. For this purpose, monthly 74 SAR images from 2017 to the end of 2022 were evaluated according to the SBAS procedure in the GMTSAR academic analysis software. In order to, both validate the InSAR-SBAS results and convert the deformation rate in the Line of Sight (LOS) to the ellipsoid normal direction, 3 periods of GNSS campaign were performed between 2021 and 2023 in 5 different GNSS stations and evaluated with the GAMIT/GLOBK software. According to the analyses, the land subsidence rate of up to −165 mm/year has been estimated in the KMRB, especially in the district centers of Bayındır and Ödemiş. In addition, unlike many studies, different rates and propagation of subsidence were determined in different parts of the basin depending on the aquifer type and precipitation. Monthly time series of the deformations were created and the behavior of the deformations and its relationship with the groundwater withdrawal and the lithological structure in the region was scrutinized. Thus, the spatio-temporal behaviour of the land subsidence and the associated geological factors were revealed.
- MakaleYalnız künye2020Validating InSAR-SBAS results by means of different GNSS analysis techniques in medium- and high-grade deformation areas
Yalvac, Sefa
This study aimed to validate the interferometric synthetic aperture radar (InSAR) method by using relative and absolute Global Navigation Satellite System (GNSS) techniques. In this context, two land subsidence areas, one high (Mexico City) and one medium (Aguascalientes), were monitored between 2014 and 2018 by using Sentinel 1A satellite data. The monitoring was carried out with the Small Baseline Subset (SBAS) technique using 46 images for Mexico City and 18 images for Aguascalientes. Concordantly, the GNSS Continuously Operating Reference Station (CORS) data in the regions were analyzed with relative and Precise Point Positioning (PPP) GNSS analysis techniques. The time series obtained from three different analyses were compared and the results were evaluated in light of statistical criteria. According to the results, it is determined that the InSAR-SBAS technique can vary up to ± 20 mm from the displacement values obtained from GNSS due to various noise sources. Such deviations were limited to a few samples, and in general the differentiations were reasonable in the range of 7–8 mm. The difference between the deformation velocity estimation results obtained from the three different methods varied between 3 and 10 mm/year. In this context, these findings suggest that the InSAR-SBAS technique is an effective method for monitoring land deformation with the accuracy of sub-centimeter decided. In addition, PPP which has become an increasingly popular technique showed fast and reliable results in the range of 5–10 mm for InSAR verification. Moreover, with this study, most current results for Mexico City, which is the world’s fastest subsiding metropole, were achieved. In the central region of the city, the detected 300 mm/year of subsidence rate was updated as 370 mm/year. In addition, Aguascalientes was monitored by using the Sentinel 1A satellite mission for the first time in this study. The 60 mm/year subsidence rate obtained for Aguascalientes in previous studies was updated and it was estimated that there are zones where this rate reaches up to − 115 mm/year levels. In this regard, it was concluded that the deformation rate has increased for both regions since the previous monitoring studies.