“Spaceborne radar remote sensing: hydrogeological events monitoring and future
developments”
Summary
Nowadays, the use of InSAR (Interferometric Synthetic Aperture Radar)-derived products for hydrogeological events monitoring and mapping is well established in the scientific community and began to be recognized as a valuable tool for risk management and reduction by administrative entities and Civil Protection authorities.
In this PhD thesis the potentialities and drawbacks of the interferometric technique have been presented and then exploited to define three different procedures, applied in different environment and at different scales, for the use of multi-band PSI products. This thesis work represents the main outcome of a three years-long activity at the Department of Earth Sciences of the University of Florence and its goal is to test and evaluate the potential and applicability of space-borne SAR data, processed by means of different PSI approaches, as operational tools for the characterization of geohazards in different geological and geomorphological environments.
Three test sites were presented to show different approaches aimed both at reconstructing the deformation history of ground motions (mainly related to subsidence and landslides) and at evaluating the impact of the detected active deformation areas on elements at risk (public and private infrastructures, cultural heritage, etc…). Moreover, a methodology for the automatic analysis of deformation time series acquired over large areas was proposed.
The core of the thesis hinges on illustrating different methodologies that could be merged in one single work flow to detect areas of active motions, characterize them in detail and cross-correlate the satellite data with subsurface or geomorphological information, implementing the obtained products and results in the Civil Protection chain.
The Tuscany case study represent an example of integration between PSI products, used to highlight abrupt trend changes in the deformation time series of PS points acquired with high temporal frequency above the whole region, administrative entities and Civil Protection Authorities. The final output of this methodology is a classified map of the Tuscan municipalities that is intended to be used as a “priority list” for the authorities in charge of hydrogeological risk management.
The Canary Island case study proposed a methodology for the fast estimation of the impact of active deformation on the structure and infrastructures of a territory. An active area can be defined on the basis of aggregating laws directly working on the PS datasets or applying a data mining algorithm as proposed in Chapter 4. The final product of this methodology is a map in which the territorial unit (i.e. municipalities), in which the area of interest is subdivided, are classified on the basis of the presence of both clusters of active motion PS (ADA) and elements at risk ranked according to their Strategic Vulnerability.
These two case studies describes methodologies with similar outputs (municipality classification and “risk” ranking) that starts from different PSI inputs. On one side, a methodology based on a complex data mining procedure, on the other side an approach designed for being reproduced in a GIS environment.
A detailed scale analysis of the PSI product correlated with subsurface or geomorphological information is required to outline the most hazardous areas. In this terms, the Pisa case study illustrates the work flow to be followed to fully characterize a geohazard, using InSAR products derived from different bands and geological information.
Thus, the proposed case studies are intended as examples, although referred to different environments and geohazards, for the working approaches to be used for moving from the regional to the detailed scale. The idea is to start from a PSI dataset composed of thousand measurement points and recognize, using automatic and semi-automatic procedures, those areas that show high deformation rates or anomalous change in their temporal behavior, evaluating also their impact on infrastructures and so on the population. The most hazardous areas, defined in accordance also with the Civil Protection entities or with the authorities in charge of the hydrogeological risk reduction and management, are then characterized in detail.
Concluding, PSI data demonstrated their suitability for different activities dealing with geohazard investigations (mapping and monitoring), for different typology of event (landslides, subsidence and anthropic-induced phenomena), for different end users in charge of risk management (regional authorities, Civil Protection Department) and in different stages of the risk management (real time and deferred time).
