## 1 Introduction  
High precision geodetic measurements with coarse-to-fine spatial and temporal resolutions significantly complement geological, seismic, and geotechnical investigations and characterizations of geodynamic processes related to natural and human-induced activities. The continual development of synthetic aperture radar (SAR) technology and the dedicated suite of processing tools over the past years have introduced numerous opportunities in the fields of remote sensing and civil engineering. Interferometric SAR (InSAR) and advanced differential InSAR (A-DInSAR) are relatively new geodetic techniques in these fields which have proven their capability of providing centimeter- to millimeter-level change records of terrain topography and surface deformations. SAR pixel-based derived classifications and measurements promote it from the sparse point Global Positioning System (GPS) technology, while processing both SAR amplitude and phase information make it unique and advantageous over conventional imaging techniques. The DInSAR technique utilizes the phase information contained between two complex SAR images captured in different times over the same region and forms an interferometric pair. However, these acquired images must share almost the same geometry in order to obtain coherent interferometric pairs that are useful for digital elevation model (DEM) generation or deformation detection, mapping, and monitoring. Decorrelations [1,2] related to atmospheric perturbations in different acquisitions, system noise signal, reference DEM, orbit and baseline inaccuracies are common sources of errors in conventional DInSAR. A-DInSAR also known as multitemporal InSAR (MT-InSAR) and time series InSAR (TS-InSAR) has been developed to overcome these problems. Two general approaches exist nowadays. The Permanent Scatterer InSAR (PS-InSAR) is based on a single master-slave configuration [3]. Many algorithms were developed for this purpose using the same principle. The Small BAseline Subset (SBAS) utilizes the small baseline separation between different interferometric pairs allowing multiple master-slave configurations [4]. Nowadays, these A-DInSAR techniques can be combined or merged as in the Stanford Method for Persistent Scatterers (StaMPS) algorithm [5,6]. Recently, a new method called SqueeSAR is aiming to combine both PS and DS (distributed scatterer) [7]. SAR image pairs have been utilized to generate high-resolution DEM [8, 9, 10] covering large areas with low costs and high precision. The DInSAR technique has also been successfully employed in several studies for large earthquakes [11, 12, 13, 14] and the utilization of the coherence difference in earthquake damage assessment and liquefaction mapping [15, 16, 17, 18]. Particularly, A-DInSAR techniques can determine spatiotemporal deformation patterns related to tunneling-induced ground subsidence [19, 20, 21, 22, 23] and landslides [24, 25, 26, 27, 28, 29, 30]. Its ability to measure both vertical and horizontal displacements with sub-millimeter level accuracy has been proven. While above listed applications are based on the SAR phase information, its application for studying vegetation, soil moisture content, or terrain classification are based on the radar's capability to reflect the dielectric property of the ground target. In South Korea, the popularity of SAR data and InSAR techniques in both remote sensing and civil engineering fields has made important contributions in understanding the most recent geological hazards and environmental disasters that posed threats both to infrastructure and public safety. Processing of commercial SAR data acquired by TanDEM-X satellite mission has provided the extraction of high-resolution DEM [31, 32] and precise topographic change [33]. InSAR also permitted the study of the deformations induced by several geophysical phenomena in the Korean Peninsula, such as the two reported largest earthquakes in 2016 [34] and in 2017 [35] and vertical land motion due to sea level rise [36].