Inflection-based modeling of temporal and spatial deformation dynamics in mining sites using Sentinel-1 InSAR time series
Acta Geodaetica et Geophysica, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s40328-026-00518-0
- Dergi Adı: Acta Geodaetica et Geophysica
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Geobase, Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Earth, Atmospheric, & Aquatic Science Collection (ProQuest)
- Anahtar Kelimeler: Inflection-based modeling, InSAR time series, Monitoring mining deformation, Spatial deformation
- Sivas Cumhuriyet Üniversitesi Adresli: Evet
Özet
Monitoring surface deformations is critical for disaster risk management, infrastructure safety, and the sustainable utilization of natural resources. This study analyzes deformations' temporal and spatial characteristics in an active mine site with a new methodology using Interferometric Synthetic Aperture Radar (InSAR) periodic deformation time series derived from Sentinel-1 satellite data. It is seen that linear modeling approaches of InSAR time series, which are widely used in the literature, are inadequate in representing multi-stage and complex deformation processes. Based on this deficiency, in the study, inflection points (sudden breaking moments in the deformation trend) where the curvature direction changes in the deformation time series are determined, the data is divided into two sub-periods, and separate curve fitting models are applied for each period. Separate curve-fitting models were subsequently applied to each segment. Additionally, spatial deformation trends were revealed by analyzing the time series of deformation velocity and areal density ratios generated by classifying deformation rates. The developed approach aims to contribute to understanding the evolutionary processes of deformations and enhancing early warning and site safety systems by representing deformation dynamics with higher accuracy than conventional models.