Abstract
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.
Highlights
In recent decades, both high-resolution digital photographs and structure from motion (SfM) software have enabled the generation of high-quality topographic information
In order to monitor active deformation in the mud volcano area, a local global navigation satellite system (GNSS) network was created according to the criteria described by De Guidi et al (2017), in particular ensuring (i) the basic requirement of spatial and temporal stability, (ii) absence of possible gravitational instabilities in both static and dynamic conditions at sites, and (iii) a panoramic and elevated position for the theodolite total station (TST)
When the threshold of 60 % is exceeded, there are no significant improvements (Fig. 12). This result has been confirmed in all campaigns
Summary
Both high-resolution digital photographs and structure from motion (SfM) software have enabled the generation of high-quality topographic information. Among the deformation monitoring systems, the photogrammetry technique from unmanned aerial vehicles (UAVs) is becoming more widely used thanks to the high efficiency in data acquisition, the low cost compared to traditional techniques and the acquisition of high-resolution images (Harwin and Lucieer, 2012; James and Robson, 2012; Westoby et al, 2012; Fonstad et al, 2013; Javernick et al, 2014; Johnson et al, 2014; James et al, 2017a, b, 2020) This technique is important for studying catastrophic natural events such as floods, earthquakes, landslides, etc. The precision of the resulting data is controlled by other variables, such as the focal distance of the camera, flight path and flight altitude, the orientation of the camera, the picture quality, the processing chain, and the category of UAV system (fixed or rotary wings)
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