This study is to demonstrate the ability of C-band Synthetic Aperture Radar (SAR) satellite data to extract the coastline and monitor coastal erosion against ancillary information extracted by the Unmanned Aerial System (UAS)-based Light Detection and Ranging (LiDaR) measurements. Experiments are carried out on a key data set collected over the Ionian coast of Basilicata region, in the South of Italy. Preliminary results demonstrate the added-value provided in the framework of coastal area observation by integrating spaceborne radar and drone-based optical sensor technologies.

This study focuses on a very complex environment, namely the Ionian coast of the Basilicata region, Southern Italy, which includes different kinds of beaches, river mouths and built-up areas. This complex environment is used as a test case to analyze the time variability of the coastline using measurements that were remotely sensed by the satellite European Copernicus Synthetic Aperture Radar (SAR) mission. First, the accuracy of the coastline, extracted by the SAR, is discussed with respect to finer-spatial-resolution drone-based light detection and ranging (LIDAR) measurements. Then, a time series of SAR dual-polarimetric measurements acquired by the European Copernicus mission is used to discuss the time variability of the coastline of the area of interest in a time period spanning from 2015 to 2021. The experimental results show that the accuracy of the SAR-based coastline is better than 15 m, which is reasonably good precision for monitoring the erosion/accretion processes that characterize the area of interest at a moderate scale. The estimated time variability of the extracted coastline suggests a dominant erosion process, which is always within 60 m.

In this work, Multi Temporal Interferometry techniques (MTI) based on advanced synthetic aperture radar differential interferometry (A-DInSAR) have been investigated for the monitoring of deformation phenomena in slow kinematics. A-DInSAR methodologies include both Coherence-based type, as well as Small Baseline Subset (SBAS) that Permanent Scatterers (PS). These techniques are capable to provide wide-area coverage and precise, spatially dense information on ground surface deformations. MTI techniques have been applied to the town of Stigliano (MT) in Basilicata Region (Southern Italy), where the social center building has been destroyed after the reactivation of a known landslide. A direct comparison of the results has been shown that PS and SBAS techniques are comparable in terms of obtained coherent areas and displacement patterns, with slightly different velocity values for individual points. In particular, PS furnished a range of velocity between −5/−25 mm/year, while for SBAS we found values around −5/−15 mm/year. Furthermore, on the crown of the landslide body, a Robotics Total Station measuring distance values on 24 points has been installed. The displacement values obtained are in agreement with the results of the MTI analysis, showing as these techniques could be a useful in the case of early-warning situations.

During the landslide emergency many kinds of data, even if preliminary, can help to better understand the complexity of the investigated phenomenon and to give a valid contribution to the successive damage valuation. The electrical resistivity tomography (ERT) method was applied for investigating the deep characteristics of a landslide body that occurred in March 2006 close to Potenza town in Basilicata region (southern Italy): the landslide slid on a road near some farmers’ houses which had to be evacuated. The information obtained by the application of this indirect technique appeared to be particularly useful for end users involved in the risk management. The high resolution of the 2D ERT technique allowed the detection of possible sliding surfaces and the characterization of high water content areas in which the increase of the saturation degree and of pore pressures could cause a weakening of the slopes and a reactivation of the movement. Due to the comparison between ERT results and stratigraphical data from boreholes carried out in the area it was possible to decide on the adoption of other evacuation decrees.

Rockfalls represent a significant geohazards along the SS18 road of Basilicata Region, Italy. The management of these rockfall hazards and the mitigation of the risk require innovative approaches and technologies. This paper discusses a hazard assessment strategy and risk mitigation for rockfalls in a section of SS118, along the coast of Maratea, using LIDAR technique and spatial modelling. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results of the simulations were used to define the intervention actions and engineering strategy for the mitigation of the phenomena. Within two months, 260 linear meters of high-energy rockfall barriers for impact energies up to 3000 kJ were installed. After that, according to road authority, the SS18 road was opened in a safe condition. The results represent a valid cognitive support to choose the most appropriate technical solution for topography strengthening and an example of good practice for the cooperation between innovative technologies and field emergency management.

This work explores three years of geochemical signals recorded by Pieschi station (Southern Italy). The measuring station is located in a thermal spring located in the Southern Apennines Chain, one of the most seismically active areas of the Mediterranean region. The spring is located close to a geophysical monitoring network installed in 2001 by IMAA-CNR. The probe is able to record temperature and water conductivity with a sampling rate of 10 min. From November 2001 to February 2005 several anomalous variations of water conductivity were recorded. Correlation analysis with selected local earthquakes was carried out to identify events inducing strain effects in the investigated area.

Multiresolution wavelet analysis of self-potential signals and rainfall levels is performed for extracting fluctua- tions in electrical signals, which might be addressed to meteorological variability. In the time-scale domain of the wavelet transform, rain data are used as markers to single out those wavelet coefficients of the electric sig- nal which can be considered relevant to the environmental disturbance. Then these coefficients are filtered out and the signal is recovered by anti-transforming the retained coefficients. Such methodological approach might be applied to characterise unwanted environmental noise. It also can be considered as a practical technique to remove noise that can hamper the correct assessment and use of electrical techniques for the monitoring of geo- physical phenomena.

Geoelectrical fluctuations measured in seismic areas have been attributed to stress and strain changes, associated with earthquakes. The complex nature of this problem has suggested the development of monitoring stations in order to perform geophysical monitoring for a long time period and with a high sample rate. In this paper, anomalous geoelectrical fluctuations of SP signals recorded in the S. Loja basin, Lucano Apennine chain by Tito and Picerno stations, and linked with seismic activity, are analyzed and discussed.

The results of a geoelectrical survey in the Study of recent activation landslides in the Lucanian Apennine chain (Southern Italy) are discussed in this paper. During the last two years, after meteorological conditions which affected Southern Italy and in particular Basilicata Region. many landslides Occurred in this area as reactivations of old movements. These reactivations seriously damaged buildings and infrastructure and they threatened the safety of the people living in the area. Taking into account the complexity and danger of the phenomena, some evacuation decrees for a few houses were adopted. In a short time and at low cost, by Using the Mobile Laboratory of IMAA for geophysical measurements, active geoelectrical investigations were carried out and data processing performed using innovative techniques for data inversion. The results represent a valid cognitive support to choose the most appropriate technical Solution for strengthening of the slopes and an example of best practice for the cooperation between the Civil Protection of Basilicata Region and IMAA-CNR.

This paper presents the preliminary results analysing the correlation between local seismicity and geoelectrical, hydrogeological and geochemical signals concomitantly recorded in Basilicata Region, one of the most seismically active areas in Southern Italy. The signals were recorded by two stations: Tito and Tramutola. Tito station measures vertically the Self-Potential field (SP) by an array of five no-polarizable electrodes equally spaced with the common electrode at 20 m depth as well as water-level, water-temperature and electrical-conductivity. Tramutola station measures self-potential signals in soil surface, gas flow and water temperature in a thermal-water well, as well as atmospheric barometric pressure and ambient temperature. Correlations were found between the sharp variability of the signals recorded by both stations and the seismic sequence that occurred on September 3 to 4, 2004, allowing us to link these anomalies with the tectonic evolution of the investigated area.

A geoelectrical monitoring activity has been carried out to improve the geological and hydrogeological knowledge about the Varco d'Izzo landslide (Potenza, Basilicata, Southern Apennine, Italy), an active rotational–translational slide evolved in earth-flow. In this work we have focused on the Self-Potential (SP) method by applying three different SP measuring techniques and combining modern technologies for data acquisition and new methods for tomographic inversion. A SP map and three static SP tomographies have been carried out to better analyse the groundwater circulation system and to better reconstruct the geometry of the landslide body. In the accumulation zone, which is the area more exposed to the geomorphological activity, a new SP measuring strategy has been applied. This strategy, based on time-continuous 2D SP tomographies, helps identify water flow changes in subsurface by studying the time series of SP tomographic images. The analysis of time-dependent changes of water infiltration in near surface is the key to better understand the hydrogeological processes underlying the ground instability phenomena. The time-lapse analysis of tomographic images has allowed us not only to investigate the correlation between the temporal changes of SP signals and rainfall events, but also to quantify the range of these changes. The modification of the distribution of the SP source accumulation zones is associated with the dynamics of the groundwater flows. These preliminary results allow us to consider the SP tomographic method as a tool for geophysical monitoring of landslide areas and encourage to develop new measuring systems for near-real time applications.

The Val d Agri area is well-known for oil exploration. An old 500 m deep exploration well in the northern part of this area has been used for long-term hydrogeochemical investigations. The well is characterized by a discharge of about 500 L/min of thermal water (27.8°C) and a simultaneous methane gas emission of about 200 L/min. Gas analyses gave evidence that the methane come from a multiple deep reservoir. Continuous records of gas emission showed some anomalous variations occurred during the past three years. The gas flux anomalies were in a distinctive coincidence with self-potential anomalies of one station close to the hydrogeochemical station. The present paper describes the interpretation of these anomalies in relation to the geodynamic activity in the area.

Multifractal fluctuations in the time dynamics of geoelectrical data, recorded in a seismic area of southern Italy, have been revealed using the Multifractal Detrended Fluctuation Analysis (MF-DFA), which allows to detect multifractality in nonstationary signals. Our findings show that the geoelectrical time series, recorded in the seismic area of southern Apennine Chain (Italy), is multifractal. The time evolution of the multifractality suggests that the multifractal degree increases prior the occurrence of earthquakes. This study aims to propose another approach to investigate the complex dynamics of earthquake-related geoelectrical signals.

Fractal tools have been used to investigate the time dynamics of hourly self-potential data, recorded during the year 2001 by five geoelectrical stations located in one of the most seismic areas of southern Italy. Scaling behaviour has been revealed by means of different statistics: the Lomb Periodogram method, the Detrended Fluctuation Analysis, the Higuchi analysis and the mean distance spanned within the time L. The values of the scaling exponents estimated by means of these methods indicate that the temporal fluctuations of the geoelectrical signals are not typical of purely random stochastic processes (i.e. white noise), but evidence the presence of long-range correlations. Furthermore, it is found that these correlations are linear.

In the present paper we analyse the series of extreme events in geoelectrical signals recorded at the monitoring station Tito located in a seismic area of southern Italy. Applying an objective criterion to estimate the probability of occurrence of extreme events in the time series (Cuomo et al., 1996; Cuomo et al., 1997), we found a correlation between the geoelectrical anomalies and earthquakes in the area monitored during the period of recording.