Land subsidence phenomena investigated by spatiotemporal analysis of groundwater resources, remote sensing techniques, and random forest method: the case of Western Thessaly, Greece Ioanna Ilia & Constantinos Loupasakis & Paraskevas Tsangaratos Received: 22 February 2018 /Accepted: 20 September 2018 # Springer Nature Switzerland AG 2018 Abstract The main objective of the present study was to investigate land subsidence phenomena and the spa- tiotemporal pattern of groundwater resources in an area located in western Thessaly, Greece, by using remote sensing techniques and data mining methods. Specifi- cally, the nonparametric Mann–Kendall test and the Sen’ s slope estimator were used to estimate the trend concerning the groundwater table, whereas a set of Synthetic Aperture Radar images, processed with the Persistent Scatterer Interferometry technique, were used investigate the spatial and temporal patterns of ground deformation. Random forest (RF) method was utilized to predict the subsidence deformation rate based on three related variables, namely: thickness of loose de- posits, the Sen’ s slope value of groundwater-level trend, and the Compression Index of the formation covering the area of interest. The outcomes of the study suggest a strong correlation among the thickness of the loose deposits and the deformation rate and also show that a clear trend between the deformation rate and the fluctu- ation of the groundwater table exists. For the RF model and based on the validation dataset, the r square value was calculated to be 0.7503. In the present study, the potential deformation rate assuming different water pumping scenarios was also estimated. It was observed that with a mean decrease in the Sen’ s slope value of groundwater-level trend of 20%, there would be a mean decrease of 9.01% in the deformation rate, while with a mean increase in the Sen’ s slope value of groundwater- level trend of 20%, there would be a mean increase of 12.12% in the deformation rate. The ability of identify- ing surface deformations allows the local authorities and government agencies to take measures before the evo- lution of severe subsidence phenomena and to prepare for timely protection of the affected areas. Keywords Surface deformation . Remote sensing techniques . Water table fluctuation . Random forest Introduction Land subsidence is referred to as a gradual settling or a sudden sinking of discrete segments of ground surfaces that usually occurs as a consequence of a number of physical and human-induced phenomena. Groundwater over-exploitation, natural compaction of unconsolidated fine-grained deposits, collapse of natural or man-made cavities, oxidation of peat-rich materials, and tectonic activity are among the most notable phenomena that trigger land subsidence (Galloway and Burbey 2011). The majority of land subsidence cause extensive defor- mations over large areas, mainly in coastal areas and Environ Monit Assess (2018) 190:623 https://doi.org/10.1007/s10661-018-6992-9 I. Ilia (*) : C. Loupasakis : P. Tsangaratos School of Mining and Metallurgical Engineering, Department of Geological Studies, National Technical University of Athens, Athens, Greece e-mail: gilia@metal.ntua.gr C. Loupasakis e-mail: cloupasakis@metal.ntua.gr P. Tsangaratos e-mail: ptsag@metal.ntua.gr