Abstract. On 24 August 2016 a strong earthquake (Mw = 6.0) affected central Italy and an intense seismic sequence started. Field observations, DInSAR (Differential INterferometry Synthetic-Aperture Radar) analyses and preliminary focal mechanisms, as well as the distribution of aftershocks, suggested the reactivation of the northern sector of the Laga fault, the southern part of which was already rebooted during the 2009 L'Aquila sequence, and of the southern segment of the Mt Vettore fault system (MVFS). Based on this preliminary information and following the stress-triggering concept (Stein, 1999; Steacy et al., 2005), we tentatively identified a potential fault zone that is very vulnerable to future seismic events just north of the earlier epicentral area. Accordingly, we planned a local geodetic network consisting of five new GNSS (Global Navigation Satellite System) stations located a few kilometres away from both sides of the MVFS. This network was devoted to working out, at least partially but in some detail, the possible northward propagation of the crustal network ruptures. The building of the stations and a first set of measurements were carried out during a first campaign (30 September and 2 October 2016). On 26 October 2016, immediately north of the epicentral area of the 24 August event, another earthquake (Mw = 5.9) occurred, followed 4 days later (30 October) by the main shock (Mw = 6.5) of the whole 2016 summer–autumn seismic sequence. Our local geodetic network was fully affected by the new events and therefore we performed a second campaign soon after (11–13 November 2016). In this brief note, we provide the results of our geodetic measurements that registered the co-seismic and immediately post-seismic deformation of the two major October shocks, documenting in some detail the surface deformation close to the fault trace. We also compare our results with the available surface deformation field of the broader area, obtained on the basis of the DInSAR technique, and show an overall good fit.

Abstract. On October 26th 2016, immediately north of the epicentral area affected by the Mw 6.0, August 24th earthquake, a strong earthquake (Mw = 5.9), with a focal mechanism showing W-dipping normal faulting, occurred at the boundary between Marche and Umbria regions (central Apennines, Italy). Four days later (on October 30th), the main-shock (Mw = 6.5) of the whole seismic sequence occurred in the same area. The central Apennines are characterized by northeast-verging thrust-propagation folds, involving Mesozoic- Tertiary sedimentary successions. During the 2016 sequence, coseismic deformation has been recorded at the rear of the Sibillini Thrust which separates the main mountain chain from the Marche-Abruzzi foothills (Fig. 1). This contractional structure has been partly dissected and/or inverted by NNW-SSE trending Quaternary normal and oblique-slip faults. The major event (October 30) induced extensive geological effects at the surface and structural damages in the broader epicentral area up to a distance of 30 km. According to the report of the Istituto Nazionale di Geofisica e Vulcanologia (SUMMARY REPORT ON THE 30 OCTOBER, 2016 EARTHQUAKE IN CENTRAL ITALY Mw 6.5, Gruppo di Lavoro INGV sul Terremoto in centro Italia 10 November 2016), the hypocenter of major event was located at 42.8322° N, 13.1107° E at a depth of 9.2 km (Figs. 1 and 2). Following the August seismic events, we installed five new geodetic points located on both sides of the principal fracture zone and carried out two campaigns of GNSS measurements, the first one at the end of September (30-09/02-10, 2016), the second one early November (11/13-11, 2016) that covered the period of the October events. In this brief communication, we provide the results of our geodetic campaigns that registered the co- seismic displacement occurred in the period between doy (day of year) 2016/274 and doy 2016/318, therefore documenting the two latter major shocks. We also compare our results with the available surface deformation field of the broader area obtained on the basis of the DInSAR technique and particularly the elaboration realized by CNR-IREA of Sentinel-1 radar imaging of Copernicus European Program of 26/10–1/11 (http://www.irea.cnr.it/index.php?option=com_k2&view=item&id=761:nuovi-risultati-sul-terremoto- del-30-ottobre-2016-ottenuti-dai-radar-dei-satelliti-sentinel-1). The comparison shows an overall good fit. It’s worth to note that these earthquakes occurred in a sector of the Central Apennines characterized by high geodetic strain-rates (e.g., D’Agostino 2014), where several continuous GNSS stations are operating.

Abstract. Active geological processes often generate a ground surface response such as uplift, subsidence and faulting/fracturing. Nowadays remote sensing represents a key tool for the evaluation and monitoring of natural hazards. The use of unmanned aerial vehicles (UAVs) in relation to observations of natural hazards encompasses three main stages: pre- and post-event data acquisition, monitoring, and risk assessment. The mud volcano of Santa Barbara (Municipality of Caltanissetta, Italy) represents a dangerous site because on 11 August 2008 a paroxysmal event caused serious damage to infrastructures within a range of about 2 km. The main precursors to mud volcano paroxysmal events are uplift and the development of structural features with dimensions ranging from centimeters to decimeters. Here we present a methodology for monitoring deformation processes that may be precursory to paroxysmal events at the Santa Barbara mud volcano. This methodology is based on (i) the data collection, (ii) the structure from motion (SfM) processing chain and (iii) the M3C2-PM algorithm for the comparison between point clouds and uncertainty analysis with a statistical approach. The objective of this methodology is to detect precursory activity by monitoring deformation processes with centimeter-scale precision and a temporal frequency of 1–2 months.

<p>Deformation effects on surface due to active geological processes are several (e.g., uplift, subsidence and shear discontinuities), these are strictly related to the source parameters and to the geomechanical properties of the surrounding rocks. In the last 20 years, remote sensing represents a key tool for the evaluation and monitoring of the natural hazards. Disasters occur when hazard and vulnerability match.</p> <p>The risk is proportional to the magnitude of the hazards and the vulnerability of the involved population. Among the deformation monitoring systems, photogrammetry technique from Unmanned Aerial Vehicles (UAVs) is spreading thanks to the high efficiency in data acquisition (time span, resource, and operators), low cost and the capability to acquire high-resolution images. The use of UAVs in contexts of natural hazard presents three main steps for risk assessment: pre-post event data acquisition, emergency support and monitoring. The mud volcano of Santa Barbara (Municipality of Caltanissetta, Sicily, Italy) represents a potentially dangerous site. On 11th August 2008 a paroxysmal event caused serious damage to infrastructures for a range of about 2 km. The main clues of mud volcano paroxysmal events are the uplift and the development of structural features with dimensions ranging from centimetre to decimetre. Here we present a methodology for monitoring of deformation processes that may be precursors of the mud volcano unrest period. This methodology is based on: i) the data collection, ii) the Structure from Motion (SfM) processing chain and iii) the M3C2-PM algorithm for the comparison between point clouds and uncertainty analysis with a statistical approach. This methodology is useful to detect hazard precursors by monitoring of deformation processes with centimetre precision and a temporal frequency of 1 - 2 months. Precision maps and the M3C2-PM algorithm are used to determine surface variations. The statistical analysis allows us to verify i) the uncertainty between the different surveys ii) the spatial variability of the accuracy; iii) the quality of the georeferencing of the surveys based on the number of GCPs (ground control points).</p>