## 5 Discussion
### Potential and Challenges of Big Data
In this regard, in the GEP, the selection of parameters such as the number and acquisition date of the input SAR data, the study area (clip to AOI), the processing thresholds (e.g., temporal coherence), and the location of the reference point, is allowed through the geo-portal within the framework of a consolidated and standardized P-SBAS processing routine. In the case of Capo Colonna and Crotone, this functionality has definitely been advantageous compared to previous studies that exploited already processed and ready-to-use InSAR datasets [28; 39; 46]. At equal opportunity of reliance on trustable InSAR datasets produced by means of consolidated processing routines, in the present experiment, we could tailor the processing parameters to suit our purposes (e.g., reference point selection and respective implications, as discussed in Section 5.1.3). On the other side, compared to those papers investigating land subsidence and regional tectonics in the study area based on InSAR products generated by the authors themselves [38; 45; 46], the processing times achieved thanks to the use of the GEP were extremely short on a relative scale, especially when considering that the Sentinel-1 stacks used in the present study were one order of magnitude longer (i.e., 300 vs. 40-60 images). A drawback is, of course, due to the current limitations in the range of SAR sensors that can be selected for P-SBAS processing in the GEP. At present, the P-SBAS on-demand service runs with Sentinel-1 data only, and it is also available for ERS-1/2 and ENVISAT SAR data archives via a link with the ESA G-POD platform [55]. Of course, such eased accessibility to reliable InSAR products does not solve the challenge of how to manage the post-processing and geospatial analysis of hundreds of thousands (or even millions) of coherent points. In the present research, given the intended demonstration character of this paper and the regional scale of the geohazard analysis (therefore, with no intention to deepen the geological interpretation beyond the correlation between the observed motions and the type of natural and/or anthropogenic process), the multitude of coherent points was creamed-off by narrowing down the geological interpretation to a relatively small region of 300 km\({}^{2}\), and to its most relevant displacement patterns. This was done based on the initial LOS velocity values and the extracted vertical and horizontal displacement field, and then through geospatial integration with ancillary data (e.g., lithological map, landslide inventory) and the literature (e.g., evidence from previous InSAR studies). Such an approach is viable and effective when there is strong background knowledge of the geohazards affecting the study area. In other contexts, methods such as hotspot identification and clustering [94], time series analysis and estimation of trend deviations [15; 17; 95], statistical tests, and probabilistic approaches [16; 17; 18] are recommended. Research trends in the field of InSAR are now aiming toward the development of processing chains and approaches to continuously update multi-interferogram processing outputs (as well as their post-processing and automated analysis) every time that one or more new SAR scenes are available for the study area. These approaches may provide key information for monitoring and early warning of the occurrence of anomalous trends and/or acceleration associated with precursors or incipient deformation processes, and thus input alerting and operational monitoring services (e.g., [25; 96]). To achieve these goals, efficient approaches for data reprocessing after new data inputs become available are required to optimize processing loads and times (in the order of a few hours; [25]) for the updating of a multi-interferogram processing (e.g., via a sequential estimator; [97]). Currently, the P-SBAS service available in ESA's GEP does not include such functionality, and therefore the benefit of these approaches on its time performance cannot be assessed in this case.