Terrestrial and Marine Environments 2 [610442]

Appl. Sci. 2020, 10, x; doi: FOR PEER REVIEW www .mdpi.com/journal/ applsci Type of the Paper (Article ) Special Issue "3D Reconstruction and Data Analysis: Cutting -Edge Techniques for 1
Terrestrial and Marine Environments" 2
Digital field mapping and drone‐aided survey for 3
structural data collection and seismic hazard 4
assessment: the 2016 Central Italy Earthquakes case . 5
Daniele Cirillo 1-2,* 6
1 DiSPUTer Università G . d’Annunzio , via dei Vestini 31, 66100 Chieti , Italy 7
2 CRUST – Centro InteRUniversitario per l'Analisi SismoTettonica tridimensionale, Italy. 8
* Correspondence: d.cirillo@u nich.it; Tel.: +39 -0871 -355-6389 9
Received: date; Accepted: date; Published: date 10
Abstract: 11
In this work, a high -resolution survey of the coseismic ground ruptures due to 2016, Central Italy, 12
seismic sequence, performed through a dedicated software install ed on a digital device, is 13
strengthened by the analysis of a set of images acquired by drone. 14
We applied this integrated approach to two active sections of the Mt Vettore active fault segment 15
which , in the Castelluccio di Norcia plain (ce ntral Italy), wer e affected b y surface faulting after the 16
strongest events of the sequence : the 24 August, Mw 6.0, Amatrice and 30 October, Mw 6.5, Norcia 17
earthquakes. 18
The main aim is to establish the range in which the results, obtained measuring the sam e structures 19
using different tools , vary. 20
It is also propose d an operating procedure that can be helpful to map extensive sets of coseismic 21
ground ruptures especially where this latter affect wide, badly accessible , or dangerous areas. 22
We compared the dat asets collected t hrough different t echnologies, including faults attitude, 23
dip-angles, coseismic displacements , and slip vectors. 24
After assessing the accuracy of the results , even at centimetric resolutions , we conclude that the 25
structural dataset obtain ed through remo te sensing techniques shows a n excellent degree of 26
reliability. 27
Keywords: drone -acquired imagery; high -resolution topography, digital mapping; 28
compass -clinometer integrated tablet; coseismic r uptures; aero photogrammetry ; 2016 Central Italy 29
seismic sequence; virtual outcrop , Structure -from -Motion. 30
31
1. Introduction 32
33
The new technologies that replace the 20th-century field tools are the smartphone, handheld 34
GPS, tablets , iPad , and Drones. Last generation tablets, in particular, have the performances of a 35
hand -comp ass, plus take pictures and act as both a notebook and mapping device , and gather 36
precise location data using GPS. They can even be equipped with GIS software. The impressive 37
technological development characterizing th e current times have brought to signif icant 38
improvemen t also in the field mapping techniques. The “classical” geological survey can be now 39
integrated by digital mapping carried out usi ng several types of devices, like tablets with dedicated 40
software, and i n some particular contexts by the acqu isition of image s by drones [1 -14]. This work 41
provide s a workflow for drone remote -sensing and structural-geological mapping which offer 42
significant advantages compared to th e traditional fieldwork. The collected data enable us to 43

Appl. Sci. 2020, 10, x FOR PEER REVIEW 2 of 30
reconstruct three -dimension al models of inaccessible outcrops and to explore in detail areas which, 44
during a recurrent seismic activity, might be affected by rock falls (cliffs or outcrops at the foot of 45
prominent fault scarp). Furthermore, compared to the traditio nal method s which empl oy 46
compass‐clinometer and field book, digital mapping, performed eith er with tablet and/or drone, 47
allow collecting an enormously greater number of data thanks to the fast and continuous acquisition 48
procedure and the automatic geo‐refe rencing. As an exa mple , more than 400 0 survey data, as type of 49
rupture , attitude, ki nematics, slip vector (obtained from coseismic slickenlines or piercing points), 50
and displacement (throw, opening, and net displacement), were acquired along the Mt Vettore -Mt 51
Bove F ault (VB F) ove r a total length of ab out 30 km, immediately after the two major seismic events. 52
The survey was performed at a high resolution, with a sampling rate of at least one site per 50 m, and 53
locally of three sites per meter. All data reported and di scussed in Brozzetti et al . [15], has been 54
collected through the Fieldmov e app instal led on iPad dispositive . During the aforementioned 55
survey, the traditional mapping methods were supported by digital technologies, such as digital 56
field mapping and d rone -aided survey, whi ch turned out to be useful to reduce sensibly the 57
working time and to collect such massive field datasets. 58
Furthermore, the use of multiple work tools, even on the same site, has allowed us to compare the 59
effectiveness of the various appli ed me thods and, a t the same time, making cross -checks to test their 60
reliability. 61
Here we report on the results of the high -resolution structural mapping of the coseismic ground 62
deformations due to surface faulting that followed the strongest events of the 2016 Central Ital y 63
seismic sequence, which are the 24 August, Mw 6.0, Amatrice and the 30 October, Mw 6.5, Norcia 64
earthquakes. 65
In this work we explored the advantage, the conditions of applicability and the limits of the 66
proposed novel approach to map and param eterize the coseismic ruptures, hundreds of meters or 67
kilometers long, occurred along two synthetic splays of the VBF herein referred to as Colli Alti e 68
Bassi (CAB) and Prate Pala (PTP) faults. The CAB had been known for a long time in published 69
geolo gical maps thanks to its excellent surface exposure; the second was unveiled by recent 70
paleoseismologic al research [16] which highlighted at least three reactivations during the Holocene. 71
Along these faults, where a detailed survey of coseismic ruptur es wa s available [15], the quality of 72
the results here obtained through high -resolution aerial photogrammetric images acquired using a 73
small -size low -cost drone, ha s been tested and discussed. 74
75
1.1. Study area 76
The study area s are located near the village of Ca stellucc io di Norcia ( 42°49'42.51"N 77
13°12'28.00"E ) in the southern part of the Sibillini Mts. chain, a deeply studied portion of the 78
Umbria -Marche thrust and fold belt in Central It aly [17 -19]. The stra tigraphy of this region includes 79
a Jurassic -Middle Miocene, shelf to pelagic, carbonatic succession, followed upward by Late 80
Miocene siliciclastic turbidites. 81
The contractional structures consist of a system of NW-SE to N -S-striking a symmetric box -folds 82
character ized by over turned eastern limbs and bounded by east -verging low -angle thrust faults, 83
Late Miocene -Early Pliocene in age [18 ,20,21]. 84
Towards E and SE, the outer basal thrust of the chain which, from N -S direction, turns southwa rds to 85
NNE -SSW dire ction, cau ses the supe rposition of the Sibillini thrust sheet on the Messinian Laga 86
basin turbidites . 87
Since the Early Pleistocene, extensional fault systems displaced the contractional structures 88
[22-24] with associated offset , along the single faults, locally exce eding 1500 m. De spite the fault 89
system show a certain geometrical complexity, on the whole, the Quaternary normal faults appear 90
arranged in a quite a regular, NNW -SSE-striking regional alignment across the Umbria -Marche and 91
Laga domains . 92
During t he Quater nary, the activi ty along the major ext ensional faults, which dip to W -SW, led to 93
the formation of intra -mountain basins, filled with alluvial and lacustrine deposits [25 -27]. 94

Appl. Sci. 2020, 10, x FOR PEER REVIEW 3 of 30
The easternmost extensional fault, the VBF , is a highly segmented, well -known active structure 95
with a 6.5 ≤ Mw ≤ 6.8 maximum expected magnitude [28] (Figure 1a). It shows an along -strike length 96
of ~30 km, a long -term maximum displacement of ~ 1500 m [21,25,29], and a maximum Late 97
Quatern ary slip rate of 1.3mm/y [15]. 98
The Piano Gra nde basin developed in the VBF hanging wall during the Middle -Late Pleistocene 99
(Figure 1b). Eluvial -colluvial deposits overlay unconformably the carbonate bedrock along the 100
borders of the basin whereas the major depression is mainly filled by alluvial and lacustrine 101
sediments [30 -31]. 102
Well before the 2016 Central Italy seismic sequence, the present activity of VBF had been 103
suggested on the base of the observed displacement of Quaternary deposits and Late Ple istocene – 104
Holocene landforms [21,23,25]; subseque ntly its seismogenic potential was highlighted by 105
paleoseismological evidence [28]. 106
The diffuse surface faulting observed along the VBF after the 2016 sequence (Figure 1b) and the good 107
correlation between the activated fault at the surface and the hypocen tral distribution of the 108
seismicity, unquestionably confirmed the seismogenic role of this fault. 109
110
111
112
Figure 1. (a – top-right inset ): location map of the study area in the central Apennines of Italy (a – main figure) 113
Structural sketch of the Mt Vettore-Mt Bove fault (VBF) , with epicenters (red stars) and focal mechanism of the 114
three M>5.5 earthquakes of the 2016 seismic sequence , according t o Chiaraluce et al [32]; Geological key color – 115
green: Umbria-Marche Domain, brown: Laga Domain, yellow: Quaternary deposits; 116
(b) Geological map of the study area, after Pieranto ni et al. [29], modified, and location m ap of the two sample 117
areas (1 and 2) where the Colli Alti e Bassi (CAB) and e Prate Pala (PTP) splays of the VBF crop out; top -left 118
inset s hows the stratigrap hic scheme of the area extracted from Pierantoni et al. [29]; MAS: Calcare Massiccio; 119
BUG: Bugarone Group; COI: Corniola; RSA: Rosso Ammonitico; POD: Calcari a Posidonia; CDU: Calcari 120
Diasprigni; MAI: Maiolica; FUC: Marne Fucoidi; SBI: Scaglia Bianca; SAA: Scaglia Rossa. 121
122
All the three main segments in which the VBF is divided activated during the 2016 seismic sequence; 123
they are referred, f rom south to north, to as the Vettoretto -Redentore, Bove -Porche and C upi-Ussita 124
segments [15]. 125
Several synthetic a nd a ntithetic splays bran ch from the three segments at distance up to 4 km west of 126
the main fault trace. 127

Appl. Sci. 2020, 10, x FOR PEER REVIEW 4 of 30
Two of the major splays of the Vetto retto -Redentore segment, located along the eastern border of the 128
Piano Grande di Castelluccio basin , and named here inafter the Colli Alti e Bassi Fau lt and Prate Pala 129
fault ( CAB and PTP respectively, Figure 1b) were affected by significant coseismic reactivation and 130
have been stu died in detail in this work. 131
132
1.2. D istribution of the Coseismic ruptures 133
The 24 August, M w 6.0, Amatrice earthquake [32 ,33] caused the reac tivation of the 134
Vettoretto -Redentore segment of the VBF [VRS, Figure 1a -b, 15 , 34, 35]. The 26 October (M w 5.4 and 135
Mw 5.9) and 30 October ( Mw 6.5) event s continued the reactivation of the VBF causing respect ively 136
the rupturing of its northern (Cupi -Ussita) and central (Bove -Porche) segments and reactivating 137
again the Vettoretto -Redentore segment. 138
Massive field surveys performed by several re search groups after the three earthquake s, allowed to 139
reconstruct an d compile very detailed databases of the associat ed primary ruptures [15 ,36-38]. 140
To date, most authors [15 , 39-41] agree that: i) the M w 6.0 event caused surface fa ulting, along a ~ 6 141
km section of th e VRS, with coseismic throws reaching 27 cm, without ac tivating any other splay of 142
VBF; ii) the 26 Octob er M w 5.9 event ruptured the only northern segment of the VBF, (Cupi -Ussita), 143
with throws ranging from 8 to 10 cm; i ii) the 30 October (M w 6.5) mainshoc k re -activated and 144
ruptured the entire Vettoretto -Reden tore and Bove -Porche segment, with a surface rupt ure length 145
32>L>22 km and coseismic surface displacements up to 222 cm, and iv) despite most of the 30 146
October coseismic ruptures occurred along the mai n fault trace, they partially reactivated also 147
syntheti c and antithetic splays within a few kilomet ers off the main fault trace. On the contrary, n o 148
evidence of coseismic rupture was observed after the 24 August eve nt along the subsidiary 149
structures . 150
151
152
1.3. Selection of sample areas 153
In the Castelluccio di Nor cia a rea (Figure 1b), two cases of significant cos eismic 154
fault -reactivation occurred, after the 30 October mainshock, along the Colli Alti e Bassi (CAB) 155
[(42°50'10.06"N 13°13'46.35"E )] and Prate Pala (P TP) [(42°49'10.70"N 13°13'23.15"E )] normal fault 156
(Figure 1b). The CAB geologic (i.e. long term) expression was previously recognized a nd reported in 157
published geological maps [21 , 29]. 158
The PTP was recog nized and partially mapped by Galadini and Galli [ 42] through an aerial 159
photo -geologic survey, integrated by paleoseismological trenching. 160
Both these reactivate d synthetic splays of the V RS, crop out c lose to the eastern border of the 161
Piano Grande basin . We se lected the sample area 1, straddling the CAB, and the sample area 2, 162
including t he PTP ruptured during the 2016 mainshock. 163
In neither area evidence of ruptures were detected after 24 August and 26 Oc tober events (Figure 164
3a-b-e), thus the total measure d dis placements can be referred to the 30 October reactivat ion. 165
Digital fieldwork car ried out on bot h the sample areas soon after the mainshock, provided coseismic 166
displacement values of up to 101 cm alon g the CAB (Figure 3 c -d) and of 14 cm in the central part of 167
the PTP (Figure 3 f -g). 168

Appl. Sci. 2020, 10, x FOR PEER REVIEW 5 of 30
169
Figure 2; a ,b) Sample area 1, along the Colli Alt i e Bassi Fault ( CAB, location in Figure 1b); the two 170
sketches ( a=plan view, b= bird’s eye view) illustrates the mission flight plan for image capturing over the sample 171
area us ing a manual flight, with an overlap of 80% along the path and 80% in a lateral direction , useful to have 172
a good alignment of images and t o reduce the distortions on the resulting orthomosaics; 173
c,d) Sample area 2, along the Prate Pala Fault; (PTP, lo catio n in Figure 1b) the two sketches ( c=plan view, d= 174
bird’s ey e view) illustrates the mission flight plan for image capturing that covers the area using north -south 175
flight paths with 65% alo ng the path and 60% in a lateral direction. 176
Legend: blue point: shot point photo; yellow point: sites of manual and digital mapp ing; blue line: trace of the 177
CAB (a) and PTP (b) faults; tics indica tes the hanging wall block . 178
179
2. Materials and Methods 180
181
2.1. Field Ma pping 182
The high -resolution mapping of the surface coseismic ruptu res i n the field was carried out 183
integrating the traditional su rvey, performed using a g eologic compass -clinometer for measurement 184
of planar and linear elements (dip azimuth/ dip -angle of faul t planes, trend and plunge of 185
slickenlines), with digital mappin g tec hnique. The digital mapping was based on a digital 186
comp ass-clinometer App for portab le devices, allowing the direct measuremen t of georeferenced 187
planar and linear elements accompanied by w ritten notes, sk etches, and editable photographs of 188
each survey site (Figure 4). The “Fieldmove” App for smartphones, table ts, and iPad , developed by 189

Appl. Sci. 2020, 10, x FOR PEER REVIEW 6 of 30
Midland Valley & Petroleum Experts [43], Gla sgow -Edinburgh Scotland, was chosen and installed 190
on a n Apple i Pad Air2 wifi -cellular (128 GB memory) with an internal A -GPS GLONA SS. 191
Several preliminary trials allowed to verify that the internal sensor of IOS pr ovide s reliable and 192
precise azimuthal and dip-angle measures. The reliability -trials consisted of repeat ed comparisons 193
between measures of the same structure carried o ut us ing the digital device and the geological 194
compass -clinometer. This testing exper ience highlight ed that the chosen device and s oftware 195
assured accurate compass readings for both azimutha l and clinometri c measurements that not 196
exceed ±2 degrees. For the positioning of the elements measured, an internal GPS sensor A -GPS and 197
GLONASS also i ntegrated with the high -resolution images fro m the Google Earth™ Pro 7.3 was 198
successfully used. The accu racy of the wayp oints acquired depended on satellite coverage . When the 199
maxi mum satellite coverage reached the optimum values, the error estimated for the automatic 200
location was of 1 -2 meter s, whereas it reached 3-5 meters in the worst coverage conditions. The 201
solution to minimalize the error location (well below one -mete r resolution) was the manual 202
adjusting on the iPad screen, taking into account the easily recognizable elements on the Google 203
Earth base map imagery . A further precaution to a void positioning in accuracies was t he use, as 204
Fieldmove base maps, of previous ly acqu ired high -resolution images, orthorectified through 205
ArcGis, and exported from the Move software in .mbtiles or .geotiff format file. 206

Appl. Sci. 2020, 10, x FOR PEER REVIEW 7 of 30
Field data were organized in a compre hensive GIS -managed dataset for subsequent elaborations. 207
The used software aside from the Fieldmove App for Apple iPad includes Esri Arc Map 10.x and 208
Move 201 9 Petex suite [http://www.petex.com/produc ts/move -suite/ ]. All the geological -structural 209
data acquired w ere elaborated wit hin the Move suite software Petroleum Experts see sect.3.1.2. 210
Figure 3. (a-d): sample area 1 – the same outcrop of the CAB fault sc arp shoo ted at three temporal stages: a) 211
before the beginning of the 2016 seismic sequence, b) after the 24 August and 26 Oct ober events but before the 212
30 October one, and c -d) after the 30 October mainshock (bottom le ft on each image, date and the hour of photo 213
shooting) ; (e-h): sample area 2 – images at different scal es, of the coseismic surface effects of the 30 October 214
main shock along the PTP fault trace. 215
216
217

Appl. Sci. 2020, 10, x FOR PEER REVIEW 8 of 30
2.2. Georeferenced field images dataset 218
The database of georeferenced images used also for re constructi ng virtual outcrops, includes t he 219
photographs shooted du ring the digital survey, using the Fieldmove dedicated tool , and hundreds 220
of digital photographs taken through a compact Sony camera with an integrated GPS sensor. 221
Furthermore , it has been i mproved by several set of high -resolution aerial photographs acqui red 222
through a digital camera transported by a Drone (Figure 4), whose methods of acquisition and 223
processing is reported in the following section 2.3. 224
Photogrammetric processing led to elabo rate two Digital Surface Models (DSM) at centimetric 225
resolu tions for both the study -cases. 226
For their processing, different s oftwa re as Agisoft Metashape Professional 227
[https://www.agisoft.com/ ], Cloud Compare [ https://www.danielgm .net/cc/ ], Esri Arc Map v.10.x, 228
Move 201 9 Petex suite [ http://www.petex.com/products/move -suite /] were used. 229
230
Figure 4. Survey tools used during different fieldwork act ivities: above: Traditional compass -clinometer and 231
Digital device (Apple iPad Air2) supporting the “Fieldmove” App by Midland Valley & Petroleum Expert , in 232
position for the measure ment of a shear plane wi thin a fault breccia; below: Drone model DJI Phantom 3 233
Professional and details of its components; Sony camera DSC -HX5V with integrated GPS; botto m-right: 234
traditional papery field book . 235
236
2.3. Remotely acquired images and data 237
238
2.3.1. Instruments calibration and pre -drone surv ey 239
The use of cameras for the Structure Fr om Motion (SfM) and the creation of tri -dimensional virtual 240
outcrops is now very eas y and fast because the instrumentation at our disposi tion is very light to 241
transport during the field survey. 242
The nece ssity of tota l stations GPS for the acq uisition of more precis e and more accurate data 243
positioning is generally required, but in this work , we did not use it. The method used in this 244
research is based m ainly on the placement of markers Ground Cont rol Points (mGCPs) at a 245
well-defined know n distance during the field survey. The objectives of this work do not take into 246
account the accurac y in term s of positioning of the virtual outcrop in the space ( that is in terms of 247

Appl. Sci. 2020, 10, x FOR PEER REVIEW 9 of 30
absolute coordinates), but it aims at achiev ing high-precision in the measurement of the outcrops 248
parameters, as f.i. height of slope s, wid th, and length of the vi rtual outc rop, amount of coseismic 249
displacement associated with each part of the rupture. Therefore t his research proposes a method of 250
utilizin g photogrammetry for creati ng a georeferenced and scale d virtual outcrop without the use of 251
total stations GPS. The me thod is based o n the use of an mGCP s of known geometries located close 252
to outcrop during the field survey. The markers located on ou tcrops are used as ground control 253
points and their d istances are calculated. 254
The acquisitions of mGCPs are essential in the p re and post -processing ph ase, i n order to make scale 255
changes, to position, orientate and rescale the three -dimensional model in the chosen Geographic 256
Reference System. In this work 25 x 25 cm markers were used as mGCPs . They were black and 257
yellow plasti cized paper , resistant to damp and rain, fixed w ith silicon on small woo den boards to 258
obtain major stability and prevent movements due to wind. 259
During the subsequent analysis through the Agisoft Meta shape software , the placement of markers 260
(see inset Figu re 5a) were posit ioned at the center of each mGC Ps surveyed, to optimize precision 261
between the images, and for subsequent rescaling of the virtual outcrop. The contrasting black and 262
yellow rectangles allow make easi ly recognizable the common points on each acquired photo and 263
also facilitate the automat ic location of points belonging to different images. 264
The dimensions and the double col or of mGCPs made them visible from heights up to over 100 265
meters. 266
To improve the reliability of the measurement performed on a virtual outc rop, different calibers 267
oriented in the third dimension ( zy/zx plane= heigh t, yx plane= width and lengt h), perpendicul ar to 268
each other were added. 269
The caliber instruments as hand -ruler 25 met ers long , aluminum stadia graduated rod 5m long , and 270
markers posit ioned at predetermined dis tances were used. 271
This method provided good precision in evaluating the virtual outcrop parameters, but it d oes not 272
take into accoun t the absolute accuracy in terms of geographical positioning , therefore the whole 273
model could be s hifted also by some decimeters . In this work, a ll the markers were positioned at a 274
distance of 10 meters from each o ther and arranged in two preferential orth ogonal directio ns 275
North -South and West -East . 276
In the sample area 1, they were positi oned at the int ersect ion points of a 10 m sided square grid 277
oriented in N -S and E -W directions (Figures. 1b, 2a -b). Overall, in thi s area, 15 mGCPs, 7 of which in 278
the fault footwall and 8 in the hanging wall, and different calibers were used for scaling the obtained 279
mode l. 280
The area 2, characterized by a narrow and elongated shape (1 x 0.13 km), to reduce the 'doming' 281
effect (eg 10, 12, 13), a total of 20 mGCPs were arranged in the fault footwall, in the hanging wall, 282
and also at corners and central part of the investigate d area (Figures 1b, 2c -d). 283
284
2.3.2. Drone Survey 285
The aircraft used to perform the survey was a quadcopter Drone that is generally thought for 286
hobbyist use and accordingly, has a user -friendly control system. It also offers several other 287
functions, such as a utopilot and auto -return home in case of loss of signal. This Drone has a fl ight 288
range of approximately 25 min with a single battery charge and flies up to 3.1 mile s (5 km) from the 289
controller. These charac teristics are s ufficient to cover a relatively sma ll to medium area. The Drone 290
is equipped with an autopilot package that, in the presence of internet co nnection, follows a 291
pre-programmed flight -path using the approp riate app, enabling the user to cho ose the number of 292
waypoints, the photo shooting , and t he desired flight altitude. 293
A Drone camera with sensor 1/2.3” CMOS, 12. 4 M Effective pixels, lens FOV 9 4° 20 mm (35 mm 294
format equivalent), Image Size of 4000×3000 was used for the survey, also for more detailed 295
resol ution, a camera Sony DSC -HX5V with 10 m egapixels and internal GPS sensor was used. 296
The flight was followed through a remote controller wirelessly connected with an Apple iPad Air 2. 297
The mission program for both the study areas included a de tailed fli ght plan, including the flight 298
direction, num ber of flight lines, flying altitude, and orientation of the camera res pect to the flight 299

Appl. Sci. 2020, 10, x FOR PEER REVIEW 10 of 30
path. The progra m w as thought taking into account that the awaited resolution of the 300
post -processing images strongly depends on the overlap, side lap, and ground samp ling distance. 301
The overlap (in flying direction) and side lap (between adjacent flight lines) were set c onsidering the 302
width parallel to the flying direction. 303
In the study area 1, a manually piloted flight-mode was carried out due to the la ck of coverage o f 304
UMTS signal causing, in turn, the complete absence of internet connec tion. The manual flight paths 305
were organized into three different acquisition method: a) three aerial strips at three different 306
altitud es: 30, 60 and 120 meters above ground level , shooting the photos perpendicular to the flight 307
direction; b) two aerial st rips very close ( 3 and 5 meter s) to the fault plane, with the oblique -oriented 308
camera ; c) two aerial strips farther from the previ ous one, with photos shooted perpendicular to the 309
outcr op (Figure 2a -b). A total of 268 photos were acqu ired, with a minimum f ront and side 310
overlapping of 80%. During half of the flight, the camera orientation was maintained perpendicular 311
to the main path whereas , for the second half -flight, a path -parallel ar rangem ent was set. The need 312
to adopt different sh ooting angles was due to the high slope -angle characterizing the outcrops of this 313
sample area . The flight tim e required to cover the entire area was 20 minutes. 314
In the study area 2, the constantly good inte rnet c onnection, allowed to plan an automatic -mod e 315
guided flight throug h a dedicated application. 316
In this case, th e flight path was planned to maintain a constant elevation of 70 m abov e ground level 317
(Figure 2c -d). In the second s tudy area , four aerial sw eeps were carried out, leading to the 318
acqui sition of 100 photos, with o verlapping (both in front and side) ranging from 60% to 65%. 319
During the flight, being this area completely flat, th e camera orientation was maintained 320
perpendic ular to the main path , and the images were acquired in automatic . The flight time required 321
to co ver the ent ire area was 15 minutes. 322
323
2.3.3. Photogrammetric processing 324
Photogrammetric processing was performed usi ng a Laptop HP Omen 17 -an002nl with 3.8 a GHz 325
(in Turbo Boost, 6 MB of cache, 4 core) Intel Core i7 -7700HQ, 32 GB RAM (2×16 GB DDR4 -2400), 326
NVIDIA GeForc e GTX 1070A (8 GB GDDR5) and SSD 512 GB PCIe NVMe M.2, running Agisoft 327
Metashape Professional Software. 328
The processing with Agisoft Metashape softwar e was necessary to obtain a spatial resolution of ~1 329
cm/pixel s for virtual outcrops reconstructi on. Digital photogrammetry , obtained from the sequen tial 330
drone -acquired overlapping images and through the use of Agisoft Metashape software led to create 331
the following elaborations : a) sparse point clouds, b) dense point clou ds, c) meshes and textures, d) 332
3D models, e) tiled models, f) DEM and orthomosaic model. 333
Figure 5, sho ws all the processing steps carried out wit h Agisoft Metashape software (details in the 334
caption of Figure 5). 335

Appl. Sci. 2020, 10, x FOR PEER REVIEW 11 of 30
336
Figure 5. workflow of the used digital photogrammetry procedure (a to g are in -sequence steps): ( a) 337
overlapping digital aerial photographs and ground control points are imported into the software package; 338
features within the images are automatically detec ted, matched and used to calcula te locations and orientations 339
of camera shooting p oints; ( b) points that have been used for the image alignment form an initial sparse -point 340
cloud (109.802 points); the inclusion of ground control points make the sparse -point cloud automatically 341
georeferen ced; ( c) point densification (multi -view stereo al gorithm): points that were manually classified as 342
representing the ground surface are exported as a dense -point cloud (over 13 Millions points); ( d) 3D model 343
construction obt ained building meshes betw een dense -point cloud, with 1,930,896 faces; (e) a tiled model is 344
obtained by interpolations of all image acquir ed during drone survey with faces of 3D mod el, the final resolution 345
is 3,75 mm/pixel; ( f) Construction of DSM containi ng all height values through rasterizing the dense -point 346
cloud or from mesh es. The obtained Digital Surface Model has a resolution of 1,00 cm/pixel; while (g) the 347
georeferenced or thomosaic with a high resolution of 3,75 mm/pixel was reconstructed interpola ting all the 348

Appl. Sci. 2020, 10, x FOR PEER REVIEW 12 of 30
photo s shooted f rom the drone. Additional datasets w ere co mputed fo r fracture mapping in a Cloud Compare, 349
ArcGIS , and Move Petex suite software. 350
2.3.4. Extraction of fault slip data from Cloud Compare 351
The Cloud Compare [http:// www.danielgm.net/cc/ ] open -source so ftware allowed to perform 352
structural geolo gical analysis of the surveyed coseismic ruptures, directly on a desktop P C. The 353
generated 3D point cloud, including more than 13 million points (Fig ure 5c and 6), georeferenc ed in 354
the previous steps, were used to rec onstruct the virtual outcrops and for t he subsequent kinematic 355
analysis on the fault planes. 356
After the processing of the CAB virtual outcrop, the surface of the ~ 15 m long fault mirror wa s 357
manually extracted from the density point cloud. 358
Using the Cloud C ompare s oftware, and particularly the plugin qFacets [44] 359
(https://www.cloudcompare.org/doc/wiki/index. php?title=Facets_(plugin) ), it was possi ble to 360
mak e observable the long -term s triae through an “interactive stereogram” (see inset in Figure 6c -d). 361
In fact , by selecting a narrow range of values of dip direction and dip angle, the plugin makes visible 362
only few facets of fault plane (i.e. as the ridges in grooves lineation s). This ap plication of interactive 363
filtering, is greatly useful to understand the trend of the lineations on the outcrop in a tridime nsional 364
space. After choosing and comparing them with the 30 October coseismic slip vecto r, measured 365
direc tly in the field (correlati ng hanging wall and footwall piercing points ), the associated net 366
displace ment was assessed. Through a "virtual compass" on Cl oud Compare the outcrop orientation 367
was determined and the us e of the "lineati on tool" allowed the measurement of the h eight and d ip 368
directions of the c oseismic slickenlines was performed. Finally, through Cloud Compare software , 369
all the extracted data obtain ed from the measurements on the virtual o utcrop, were exported in .csv 370
format file, as dip, dip -azimuth, trend and p lunge , and plotted onto stereonets for structu ral 371
analysis. 372
The described steps are shown in Figure 6, from den se-point cloud import (a) to the extrac tion of the 373
fault plane (b), to the me asurement of c oseismic elements (total or net displacement, c -g ) un til 374
export the database (h) in excel, .csv or .txt format. 375

Appl. Sci. 2020, 10, x FOR PEER REVIEW 13 of 30
376
Figure 6. The main steps carried out in Cloud Comp are (CC): ( a) dense -points cloud import ed into a CC 377
as ascii f ile; (b) select ion of the in terest features; ( c) contour and selection of all the d ense-point cloud around the 378
fault plane and extract ion, through the plugin qFacets , of all plunge and dip direction in a stereogram; ( d) from 379
the st ereogram the dip directions of the stria e, evidenced by grooves , are excluded; ( e) and ( f) picking of net 380
displacement (mm), striae attitude (trend and plunge), dip d irection and dip-ange of the fault plane; ( g) view of 381
the net displacement and the striae detected on the fault plane ; (e) expo rt all data in excel, .csv or .txt format. 382

Appl. Sci. 2020, 10, x FOR PEER REVIEW 14 of 30
2.3.5 High -resolution topogr aphic prof iling 383
To optimize the quality of the result of our topographi c analysis, we used two different software to 384
extrapolate profile s from the Digital Su rface Model which led to obt aining 1 cm resolution over area 385
1 and a resolution of 3 cm in area 2 (Figure 7a -d). In particular, serial profiling across th e coseismic 386
ruptures of both CAB and PTP fault was perfo rmed thro ugh the Esri ArcGis v.10.x “3DAnalys t” and 387
through the “Create Secti ons” tool of Move 201 9. From both the sets of profiles we estimated the 388
fault -scarp height (Figure 7a -d) 389
To compare our dig ital field data with those obtained by aero -photogrammet ric 3Dmod el, seve ral 390
fault attitudes, along t he CAB were manually collected a nd the height of the scarps measured 391
(Figure 7b). 392
The “surface cont rol” is es sential to estimate the errors between analogi cal (real outcrop) and digital 393
(virtual outcrop) measure ment data . 394
In the field, a meter stick was us ed to estimate all along the fau lt trace, the height of the scarp, 395
associated throw , and net displa cement, bo th on the long term and coseismic free face. T he slope dip 396
angle was measured using a clinometer (Figu re 7b). 397
Then, we compared the morphological h eight, the strike, the dip and d ip azimuth of the fault plane, 398
measured in the field, with those ob tained fro m the virtual outcrop 3D model. 399
The observed deviation between the height values of the fault scarp d irectly m easured in the field 400
and those extra cted from virtual outcrop never exceed 2 centimeter s (compare the deviation s 401
between the curves and the colo red dots of Figure 8b), confirming t he reliability of the reconstructed 402
digital topography . 403

Appl. Sci. 2020, 10, x FOR PEER REVIEW 15 of 30
404
Figure 7. Geor eferenced orthomosaic of CAB. ( a) Digital Surface Mod el (DSM) of CAB a nd trace of 405
topographic profi le (from 1 to 8); ( b) manual measuring o f the scarp height associated to the CAB; ( c) 406
topographic profiles obtained usi ng 3D Analyst extension of ESRI ArcGis; ( d) topographic p rofiles obtained 407
through move soft ware. 408

Appl. Sci. 2020, 10, x FOR PEER REVIEW 16 of 30
3. Results 409
3.1. Study area 1 – Colli Alti e Bass i Fault (CAB ) 410
3.1.1. Topographic analysis of CAB 411
The graphs in Figure 8 show a comparison between the measures of the Total Topographic Offset 412
(TTO = blue line), the Height of the preserved Fault Scarp (HFS =red line) and the 30 October 201 6 413
Coseismic Ruptu res (net displac ement) from Remo te Analysis ( CRRA = violet line) measured on the 414
CAB in the sample area 1. 415
The e stimated values of these features (on the Y axis, in mete rs) are plotted against t he along -strike 416
distance of each measurement p oint (abscissa) f rom the northern tip point of th e fault -scarp outcrop 417
(assumed as X= 0). 418
Dots in the Figure 8 graph mark the va lues, manually measured on the control points, respec tively 419
for the height of the fault scarp , measured with h and ruler (green dots) and the 3 0 October 2016 420
coseismic ruptures ( net displacement) from the manual survey (yellow dots). The good agreement 421
betw een the field data and the assessments obtained from t he topogra phic analysis on the virtual 422
outcrop, confirms the reliability of the adopted method. 423
The TTO and HFS curves show very similar trends but differ in several points because the former 424
includes t he part of the scarp removed by erosion. 425
Interestingl y, the CRR A curve, even if characterized by lower values , (higher observed net slip = 1. 25 426
m) shows a go od correlation with TTO and HFS curves, as regards the position of the maxima and 427
minima. This re markable consistence suggests that the along -strike height profile of the current fault 428
scarp deri ves from the add up of a certain number of c oseismic displac ements, each charact erized by 429
slip-profiles similar to the one caused by the mainshock of the 2016 sequence. 430
431
432

Appl. Sci. 2020, 10, x FOR PEER REVIEW 17 of 30
Figure 8. (a) Outcrop im age of the CAB fa ult; (b) Comparison of differ ent types of topographic pr ofiles; blue 433
line: height of long term slop e; red line: effective p resent fault scarp; violet: coseismic net d isplacement. Both 434
along -strike distanc e (abscissa) and height value s (ordinate) are expressed i n meters. Colored dots refer to field 435
measurements collected at control poin ts. 436
437
3.1.2. Structural and kinematics anal ysis of the CAB 438
During the fieldwork, sever al attitudes of the CAB were measured as a dip and dip azimuth, usi ng 439
either a tradi tional comp ass-clinometer and a Fieldmove -equipped Apple iPad. After da ta 440
collection, t he whole dataset was managed in a georefer enced digital database. 441
Subsequently , we extract ed attitude and kin ematic data from the virtual ou tcrop reconstru cted 442
through remotely acquired images (see sec. 2.3.4.) 443
A comparison betw een the three di fferently attitude dataset is shown in the plots of F igure 9. 444
445
Figure 9. Comparison between the fault attitude and stria tions trends meas ured through h igh-resolution 446
sampling on the CAB using traditional compass -clinometer (a,d), Fieldmove App on a digita l device (b,e) , and 447
virtual outcrop reconstructed fro m drone -acquired imagery (c,f). The upper p lots (a -c) shows the faul t 448
dip-azimuth; th e lower plots (d-f) shows the trend of associated striae; for each rose diagram the mean value 449
resulti ng from the stat istical analysis of the dataset is reported in the bo ttom -right rectangle Rose diagrams 450
were ext racted through Move 201 9 software and redr awn through Co rel Draw X4 sof tware. 451
The hand -compass collected dataset show s that on six measurement s on the fault plane, the tre nd of 452
dip-azimuth is variable between N220 and N260, with a mean resultant plane orien tation of 453
dip-azimuth at N237 and dip-angle of 68 degrees (Figu re 9a). In the sam e points , the measur ement s 454
with the Fieldmove app show a dip -azimuth trend on a fault plan e, comprised between N220 and 455
N260 with a m ean resultant plane orientation of dip -azim uth at N235 and d ip-angle of 70 de grees 456
(Figure 9b) . While the results obtained f rom virtual outcrop, clearly with a huge number of data (77 457
points measur ements), shows a main dip -azimuth trend between N220 and N2 40 and only a few 458
data comprised between N2 40 and N260 ; also in this last ca se mean dip-azimuth of the fault plane 459
orientation shows a trend of N233 and dip -angle of 70 degrees (Figure 9c ). 460
In order to compare the measures of stria tion trend collected through three dif ferent used tools 461
(Figure 9d -f), a number of six data were also acquired using hand -compass and Fieldmove 462
integrated compass. In both case s, the dispersion of data varies in the range between N180 and N240 463
except for the huge data extr acted fro m the v irtual outcrop that shows an at titude between N180 and 464
N220 and the mean direction dipping toward N207 , well comparable with data acquired with the 465
previous ly described tools . 466

Appl. Sci. 2020, 10, x FOR PEER REVIEW 18 of 30
As regards the determ ination of fault attitude data, t he g ood deg ree of mutual co rrelability between 467
the differently acquired data is evident and encouraging. In fact they mostly agree in providing an 468
average fault attitude of~ a 235 /70 (dip -notation value, c ompare rose diagra ms Figure 9a -c and 9d -f). 469
From su ch a point of vie w, the rem ote sensing survey is clearly advantageous, considering the large 470
number of data collected over a very short time in comparison with both the traditiona l and digital 471
field mappin g techniques. 472
473
3.2. Study area 2 – Prate Pala Fault (PTP) 474
3.2.1. Top ographic a nalysis of PTP 475
Despite the small offset associated with the 30 October coseismic rupture, the reactivation of the PTP 476
was highlighted soon after the mai nshock thanks to the displ acement of the pa ved road (S.P.47 7) 477
from Forca di Prest a to Ca stellu ccio di No rcia (Figure 3g -h). A maximum offset of 14 cm was 478
measured in the field in the central part of the coseismic rupture (Figure 3f) whose total length was 479
estimated in ~1.3 km. 480
The performed drone -aided mapping, which allowed the detection of tec tonic scarps displacing the 481
flat topography of the Castelluccio di Norcia plain, led to reconstruct a 3 cm resolution Digital 482
Surface Model (DSM). 483
DSM models el aborated using thi s technique do n ot permit to remo ve the vegetation noise. 484
Fortunately, in the studied cases, this problem was negligible because the periods in which the aerial 485
images were acquired (beginning of November 2016 and afterward in 2018), were prece ded by 486
several m onths of intense grazing with poor grass regro wth, due to very low ra infall . 487
Further process ing of the DSM allowed to explore and analyze through the functions of the A rcGIS 488
tools, the slope analysis, the shaded relief and the aspect of the fa ult scarp. 489
A set of 2 7 topo graphic profiles, perpendicul ar to the fault scarp, were dr awn to investigate the 490
morpho -structural expression of the PTP (Figure 10) and to reconstruct the along -fault coseismic slip 491
profiles, from north to south. 492
Interest ing is the syste matical cou nter-slope (i.e. dipping towards ea st, thus opposite to the fault dip) 493
topography observed west of the PTP trace, s uggesting a back tilting of the hanging wall block 494
which is coherent with the normal kinematic of the fault. 495
This observation, con firmed by t he per siste nce of a lo ng-term topog raphic scarp resistant to the 496
intense breeding and plowing pract iced in the area , provides further evidence of the present activity 497
of the PTP. 498

Appl. Sci. 2020, 10, x FOR PEER REVIEW 19 of 30
499
Figure 10. Topographic profiles generated using “3D anal yst” in the ArcGi s platform (Ort homosaic Ph oto and 500
DSM have a resolution of 3 cm per pixel. 501
502
A compari son between the along-strike DSM -derived topographic offset and the coseismic slip 503
profile is shown in Figure 11 . 504
In the first case (Figure 11a), from the northern edge o f PTP, the profile in creases with a 505
medium -high slope re aching th e maximum height where the topogr aphic sc arp is ~ 2.3 mete rs. 506
Moving sou th, the scarp shows a gradual decrease to zero at the southernmost surface tip of the PTP. 507
The observed asymmetric trend of the topograph ic offset suggests , according to M anighetti [4 5] and 508
Cappa et al. [4 6], that, during previous events , surface g round ruptures propagat ed mainly from 509
north to south. On the contrary, in Figure 11b, the trend of the coseismic slips shows an oppo site 510
triangular shape compared to the prev ious one, culminati ng at a maximum value of 14 cm (Figure 511
3f). 512
The aforesaid works [45] and [46], investigat ing the distribution of the slip along with the fault 513
segments during the cos eismic rupture, interpre ted the triangu lar shape, characterizing both the 514
profiles as due to the dynamics of rupture prop agation. 515
In part icular Manighetti et al. [4 5] show, from the analysis of several normalized displacem ent 516
profiles, th at the geometry o f the coseismic slip prof ile gives informatio n on the polarity of the 517
rupture pr opagation and the location of the epicente r from the fault tips and the point of maximum 518
displacement. 519
Brozzetti et al [15] comparing the 2016 Central Italy coseismic ruptures with the surface faulting of 520
the global ea rthquakes , agreed with the sugge stion of Manighe tti et al . [45] showing that the 521

Appl. Sci. 2020, 10, x FOR PEER REVIEW 20 of 30
coseismic slip profiles obtained from the field survey have an asym metric shape (from south to 522
north) for t he whole VBF, and also for the single VRS, VBS , and CUS segments of the master fault. 523
Similarly , the here reported data, suggest a pol arity of fracture propagation from s outh to north as 524
show n by the asy mmetry of the graphs Figur e 11b. 525
Possibly the difference in the observed polarity of propagation may depend on the hypocenter 526
locat ion and the magnitude of the earthqua kes that gave surface faulti ng. 527
Moreover, according to Tao et al. [4 7] and Iezzi et al. [4 1,48], the aspect of the surface faulting is 528
influenced by fault geometry and in particular by fault segmentation and/or change of direction 529
(bending). It is finally to take into account that this work had the opportunity to analyze only a short 530
section of the PTP fault , whose effective length is reasonably much higher than the portion ruptured 531
at the surface during the 30 October mainshock. 532
533
Figure 11. Comparison betwe en the topograph ic fau lt scarp ( a, in meters ) and the coseismi c slip profile ( b, 534
centimeters ) surveyed followi ng the 30 Octobe r 2016 earthquake (Mw 6.5) along the PTP. 535
536
In Figure 12b,c the measures of coseismic ruptures from hand compass and tablet d evice are showed 537
whereas figure 12d displays the d irection of fault scarp attitude obta ined from DSM analysis. 538
Comparing the thre e rose diagrams we observe that the coseismic ruptures mostly strike in the same 539
direction of the scar p generated from the ancient eart hquake s even if , in a few cases , they show 540
oblique directions. The fact that the coseismic ruptures are localized on the lo ng term fault sc arp, 541
suggests a preferential growth of the cent ral part of t he fault during each seismi c even t. 542
The three rose diagra ms of Figure 12b -d, reporting on the P TP attitudes measured with the different 543
meth ods, show a substantial agreement (particu larly the b -c ones) but also a certain dispersion. We 544
interpr et this latt er as due to the remarkable di fferences in the number of a cqui red data. In fact, the 545
major deviations occur when the hand compass and Fieldmove col lected data are compared with 546
data extracted from virtua l outcrops. To n otice that the 30 Octobe r coseismic ruptures w ere not 547
measur ed from DSM because the aerophotog rammetric image resolution was insufficient to detect 548
them. A lower elevation flight would have been necessary, especia lly in the areas of maximum slip, 549
but unfor tunately when thi s high -precision mission was planned, the a rea had been erased by 550
agricultura l activities, hampering the acquisition of new images useful for making these 551
measurements . 552

Appl. Sci. 2020, 10, x FOR PEER REVIEW 21 of 30
553
Figure 12. Sample area 2: p erspective 3D vie w extracted from Move Sof tware of the PTP fault scarp in the 554
Piano Grande near Castelluccio di Norcia; arrow s show the alignment of the coseismic surface ruptures; in 555
orange the fault scarp of PTP is highlighted, black rectangle s indicate the location of Figure 3f,g of coseismic 556
ruptures measured du ring the field survey after 30 October 2016 Mw 6.5 earthquake. 557
3.3. Accur acy and Precision 558
The integration of images acquired from a GPS Drone has allowed placing the virtual outcro p 559
in its geographical positi on, with some limitations in terms of absolute acc uracy . Anyhow, for most 560
of structural geology analysis, that need no very-high accuracy i n terms of geographical positioning , 561
the described method can be consi dered satisfact ory. 562
It is emphasized that this approach has to be considered only an integrati on to the “traditional” 563
structural geolo gical analysis. From the previou s sections it is evident that, in the two sam ple areas, 564
the obtained result , from aerophotog rammetrical processing and direct fiel d measureme nts, are 565
compara ble and that thei r precision is good. The maximum error measured along the fault scarps 566
was close t o 1 centimeter in the first area (CAB ), and around 1 -3 centimeters in the PTP area. Higher 567
accuracy and precision could be o btained using a differential GPS station integrated with the 568
mGCPs and geotagged Drone images. This woul d improve significantly the virtual outcrop models 569
and their accu racy in terms of geographical positioning (common ly close to few millimeters), but 570
usin g the GPS total station, cause a considerable lengthening of w ork time, as well as very high 571
survey costs, a condition which cannot frequently be accepted during routine fi eldworks. 572
There is also to consider that many sites , which may be potentially studied using the proposed 573
approach, are unreachable with bulky and heavy instrumentation . 574
In figure 13 the compar ison between methods using or not of GPS, calibers , and their combin ation 575
are shown. In our case studies the low performance of the GPS installed on the drone allowed t he 576
correct positioning in a geogr aphical s ystem , but without a centimetric or millimetric accuracy . In 577
any case, the precisio n of the height, width, and l ength of virtual outcrop was satisfactory thanks to 578

Appl. Sci. 2020, 10, x FOR PEER REVIEW 22 of 30
the cor rect use of caliber instruments. In conclusion, the results here obtained made it pos sible to 579
create a valid and reliab le model. 580
581
Figure 13. The s ynoptic diagram show s a combinat ion between Accura cy and Precision , white and red 582
circles represent the targ et, black points show an example of the measurements ; to the right of each target, a 583
schematization of an exampl e between real outcro p (black fau lt trace) and virtua l outcrop model (red fault trace ) 584
derived from aero-photogrammetric analysis is shown. 585
586
4. Discussion 587
The application of our working method to two study a reas affected by cose ismic surface 588
faulting, d uring 20 16, Central Italy seismic seq uence , demonstrates t hat the virtual outcrops mode ls 589
represent an important tool for structural -geological and geomorphological research aimed at 590
identifying and characterizing active tectonic structures. 591
Furthermore, comparing the informa tion ob tained from the morphological analy sis of the fault 592
scarp of CAB, with the confi guration of the coseismic surface fau lting of the 2016 Central Italy 593
seismic sequence , it is possible to make inferences on the rupturing hi story of the studied faults. 594
The good fit between the p rofile of the height of fault scarp and th e 2016 coseismic slip profile, 595
(Figure 8b) su ggests that the long-term fault scarp may have formed as a result of several 596
earthqua kes each causi ng a similar amount of surface d isplacement, It is also possible to infer for 597
these events comparable values o f magnitude. 598
In particular, taking into accou nt: i) the he ight of the entire fault scarp ii) the amount of the 30 599
October 2016 cosei smic slip, iii ) the geometry of the slope prof iles also including the possible ero ded 600
free face, and iv) the assumpiont that earth quakes of equal/ similar magnitude generated 601
equal/si milar dislocations (compared to 2016 one) , we hy pothesize that a t least 5 events are nee ded 602
to reach the obser ved val ues of fault scarp height. 603
Previous paleoseism ological works [16 ,49,50] highlighted several seismic events , some of which 604
caused the PTP r eactiva tion, occurred in the Pano Grande-Mt Vettore area. In particular four events 605
have been recognized in the last 8000 years, in addition to t he earthquake of 2016. These four 606
earthquakes , would have been occurred (from the oldest ): i) between IV and VI millennium BC, ii) at 607
the end of IV m illennium BC, iii ) between II and III millenni um BC , iv) between the end of III and IV 608
century AC (maybe in 270 AC). Furthermore, accepting the inferences, which implies that the 4.5 m 609

Appl. Sci. 2020, 10, x FOR PEER REVIEW 23 of 30
outcropping faul t scarp of the CAB was exhume d after the Last Glacial Maximum L.G.M. (~18.000 610
ky), a prelim inary estimate of the the slip rates, of 0.25 mm/y is obtaine d. 611
Of course, the analyzed fault scarps might have recorded a higher number of coseismic slip 612
events whi ch coul d have been followed b y erosional epis odes in a longer geological time, thus the 613
above estimate mus t be considered purely indicative. 614
Several aut hors studied the causes/effects of 2016 earthq uakes from many points of view, as 615
structu ral-geology, geo physics, seismology, paleosei smology, geomorp hology, interfero metry, 616
geodesy, hydrogeology, engineering [1 5,31,32,34,36,39,40,51-90], but onl y a few authors have 617
provided and elaborated data acquire d through drones [91-94]. Also no author p roduced image 618
analyses of coseismic ruptures employing the te chniques we propo se here. Our results, obtaine d 619
from the elab oration of high -resolution topo graphy, fit well with the data published in Villani et al . 620
[36], Brozzetti et al. [15] , and Perouse et al. [9 4] acq uired throu gh traditional or digital mapping 621
techniques . At the same time the present work has improved the de tails of the surveyed geologica l 622
features some of which were not appreciable directly in the field. Among th ese latter, the 623
degrada tion and erosion of the fa ult plane as well a s the tilting of the topographic surface , the 624
dip-angle and the off-fault width of the tilted area. 625
The here obtained results show ed that the use of the drone -derived photogrammetry presen ts 626
acceptable errors for all t hose structural-geological appl ications which need not very high precision, 627
(near centimet ric resolution) and that might be an integration to the traditional field survey . 628
629
Figure 1 4. Comparison of DEM and detailed topographic profi le obtained from: a) TINITALY/01 630
http://tinit aly.pi.ingv.it/ [95] with a resolution of 10 meter s per pixel; b) Cartografia Tecnica Regionale 631
vectorial 1:5000 scale from Regione Umbria 632
[http://www.umbr iageo.regione.umbria.it/pagin a/distri buzione -carta -tecnica -regionale -vettoriale – 633
1-000], with a resolution of 5 meter s per pixel; c) 1 centimeter per pi xel obtained from th is work. 634
635
In Figu re 14 three types of DEMs with different resolut ions (10 m, 5 m , and 1 cm) are compared. 636

Appl. Sci. 2020, 10, x FOR PEER REVIEW 24 of 30
The significant image resolution improvement of the topographic m odel obtained in this work 637
(Figure 1 4c) is evident as well as the significant improvement of the geologi cal interpretation, for 638
example in the cor rect positioning of tectonic structures. 639
High-resolution to pography allow s us to delineate with great precision the fault trace and in s ome 640
conditions, such as in th e CA B case, to identify the long term and rece nt ki nematic indicators. 641
In the cases wher e active faults displace post -LGM slopes, the applied procedur e, improve the 642
estimates of the scarp height , thus help ing to make infer ences on the ass ociated slip rate s. 643
Moreover, improving the p recision of the fault m apping (e.g. in Figure 1 4c) can, in turn, facilitate the 644
identification of the sites ai med at paleo seismological trenching. 645
5. Conclusions 646
During routine geological fieldwork , faults are gene rally surveyed on topogra phic and 647
geological maps using a tradit ional c ompass -clinometer or, when a high -resoluti on survey is 648
needed, using a digital device ( smart phone o tablet) with a dedicated application. 649
In this p aper , we have shown that the use of F ieldmove app for digital devi ce integrated with the use 650
of Drone -acquir ed imagery is a very performing combinatio n which speedily provides large sets of 651
good -quali ty data improving sensibly the topographic and geologica l mo dels that are su bsequently 652
recons tructed. 653
The presented h igh-resolution aerial survey represents the fi rst attempt to digitally reconstruct 654
recen t coseismic faul t ruptures in variable geomor pholo gical and outcrop conditions and to compare 655
them with la rge published datase ts collected thro ugh traditional and digit al m apping. 656
In the study cases, which refer t o two active splays of the Vettore -Bove Fault affected by surface 657
faulting during the 2 016 C entral Italy seismic sequence, we reconstructed the faul t traces, the heigh t 658
of the fault sc arps, the amount of associ ated coseismic slip and its along -strik e varia tions, with a 659
precision which is much high er compared to p revious literature reconstruc tions [15,29,36,37,96]. 660
For all the aforesaid parameters the est imated errors ra nge within a few centimeters, a value that is 661
well below the standards required by routin e structural geological survey and is also acceptable for 662
precision estimates of coseis mic g round deformations. 663
A complete workflow in which the entire procedure is de scribed in detail is reported. It is divide d 664
into successive steps specifying all the nec essary software and tools to be applied to obtain the 665
topo graphic model of a study area. 666
Moreover an as sessment of the precision and ap plicability of po int clouds derived by Drone i magery 667
is provided, and is also compared with the performances of the digital and analogic 668
compass -clinometer. 669
Some further possible applications of the reconstructed models on the investigated active fault, f.i. 670
slip rate e stimate or r econstruction of the rupture history is described, suggesting some possible 671
correlation s and integrations with the available p aleoseismological data. 672
The results of this work highlight that photogrammetry can cover and im prov e the map resolu tion, 673
whe re necessary, with l ow-costs compared to mor e expensive techniques like the LiDAR data 674
acquisi tion which are very costly and logistically compl ex to apply in many locations. 675
In other words, these methodologies undoubtedly can make a si gnificant step forward to geological 676
mapping and also to structural and geomorphological research. 677
They represent a field of work susceptible to have remarkable d evelopment and perspectives in the 678
near future. 679
Supplementary Materials: 680
The foll owing are available online at www.mdpi.com /xxx/s1 681
Author C ontributions: Daniele Ciril lo (D.C.) concei ved the wo rk. D.C . perfor med the fieldwork. D. C. prepared 682
the GIS geological database and the figures. D.C. c arries out the acquisition of images from Dron e. D.C. used 683
the new acquisition methodolo gies for the field survey, from traditional compass -clinome ter to tab let to 684
photogra mmetry analysis. D.C. wrote the manuscript. 685
686

Appl. Sci. 2020, 10, x FOR PEER REVIEW 25 of 30
687
Funding: 688
Acknowledgments: 689
This work, presents the m ain results of a research carri ed out by the authors in the frame of the CRUST 690
(Inter -Universitary Center for Tridim ensional Seismot ectonic Analysis https://www.crust.unich.it/ ) activities, 691
followi ng the 2016 Cen tral Italy Seismic Sequence; th is work realized thank it was supported by DiSPUTer 692
Depart men tal 60 % and Brozzetti re search 30% funds for the renewal of resea rch grant of Daniele Cirillo. I am 693
grateful to Petex who provided us the Move, 201 9.1 suite softwar e Licence. I am grateful to my supervisor F. 694
Brozzetti for the useful dis cussions, the su ggestions , and the critical review of the m anuscript. 695
696
Confl icts of Interest: The authors declare no conflict of interest. 697
698
References 699
1. Buckley, S.J.; R ingdal, K.; Naum ann, N.; Dolva, B.; Kurz, T.H. ; Howell, J.A.; and Dewez, T.J.B. LIME: 700
Software for 3 -D v isualizat ion, interpretatio n, and communica tion of virtual g eoscienc e models: 701
Geosphere, 2019 , v. 15, no. 1, https://d oi.org/10.1130/GES02002.1 . 702
2. Bonali, F.L. ; Tibaldi, A.; Marchese, F.; Fal lati, L.; Russo, E.; Corselli, C.; Savini A . UAV -based surv eying in 703
volcano -tectonic s: An example from th e Iceland rift. Journal of Structural Geology 2019 , 121, 46 –64 704
https://doi.org/ 10.1016/j.jsg.2019.02.004 705
3. Barlow, J.; Gilham, J.; Ibarra Cofrã, I. Kinem atic analysis of sea cliff stability using UAV photogrammet ry. 706
International Journal of Remote Sensing 2017, 38, 16 pg http://dx.doi.org/10.1080/01431161.2016.1275061 707
4. Cawood, A.J.; Bon d, C.E.; Howell, J.A.; Butler, R.W.H; Totake, Y.; LiDAR UAV or compass -clinometer? 708
Accur acy; coverage and the effec ts on structural models. Journal of Struc tural Geology 2017 ; 98; 67 -82; 709
http://dx. doi.org/10.1016/j.jsg.2017.04. 004 710
5. Corradetti, A.; McCaffrey, K.; De Pao la, N.; Tavani, S. Evaluating roughness sca ling properties of natural 711
active fault s urfaces by mean of mu lti-view photogrammetry. Tectonophysics, 2017 , 717, 599 -606 712
http://dx.doi.org/10.1016/j.te cto.2017.08.023 713
6. Tavani, S.; Corradetti, A. ; Billi, A. High precision analys is of an embryonic extensiona l fault -related fold 714
using 3D orthorectified virtual outcrops: the viewpoint im portance in structural geology . J. Struct. Geol. , 715
2016 , 86, 200–210. htt p://dx.doi.org/1 0.1016/j.jsg.2016.03.009. 716
7. Vollgger, S.A.; C ruden, A.R. Mappi ng folds and fractures in bas ement and cover rocks using UAV 717
photogrammetry, Cape Liptrap an d Cape Paterson, Victoria, Australia. Journal of Structural Geology, 718
2016 86, 168 -187 http://dx.doi.org/1 0.1016/j .jsg.2016.02.012 719
8. Bistacchi, A.; Balsamo, F.; Storti, F.; Mozafari, M.; Swennen, R.; Solum, J.; Tuec kmantel, C.; Taberner, C. 720
Photogrammetric digital outcrop reconstructio n, visualization with textured surfaces, an d 721
three -dimensio nal structural an alysis a nd modeling: innovati ve methodologies applied to fault -related 722
dolomitization (Vajon t Limestone, Sou thern Alps, Italy). Geosphere , 2015 , 11, 2031 -2048 723
9. Bemis, S .P.; Micklet hwaite, S.; Turn er, D.; James, M.R.; Akci z, S.; Thiele, S.T.; Bangash, H.A. 724
Grou nd-based and UAV -Base d photogrammetry: a multi -scale, high -resolution mapping tool f or 725
structural ge ology and paleoseismology. J. Struct. Geol. , 2014 , 69 (Part A), 726
pp. 163-178, 10.1016/j. jsg.2014.10.007 727
10. Jame s, M.R.; Robson, S. Mitigating systematic error in topographic models derived f rom UAV and 728
ground -based image networks. Earth Surface Proc esses and Lan dforms 2014 , 39, 1413-1420. 729
11. Johnson, K.; Ni ssen, E.; Saripa lli, S.; Arrowsmi th, J.R. ; McGarey, P.; Schare r, K.; Williams, P.; Blisniuk, K. 730
Rapid mapping of ultrafine fa ult zone topogra phy with structure from motion . Geosphere, 2014 . 731
http://dx.doi. org/10.1130/GES0 1017.1 . 732
12. James, M .R.; Rob son, S. Straightforwa rd reconstruction of 3d surfaces and topography with a camera: 733
Accuracy and geo science application. Journal o f Geophysical Research: Earth Surface 2012 , 117, 17pp. 734
13. Wes toby, M.J.; Brasington, J.; Glasser, N.F.; Hambrey , M.J.; Re ynolds, J.M. ‘Structure -from -motion’ 735
photogrammetry: A low -cost, effective tool for geoscien ce applications. Geomorphology 2012 , 179, 736
300-314. 737

Appl. Sci. 2020, 10, x FOR PEER REVIEW 26 of 30
14. McCaffrey, K.J.W.; Jones, R.R.; Holds worth, R.E.; Wil son, R.W.; Clegg, P.; Imber , J.; Holliman, N. Trinks, I.; 738
Unlocking the spatial dimension : Digital technologies and the future of geoscience fieldwork . Journal of the 739
Geological Society, London , 2005, 162, p. 927–938, doi:10 .1144/0016 -7649 05-017 740
15. Brozzetti , F.; Boncio, P.; Cirillo, D.; Ferrarini, F .; de Nardis, R.; Testa, A. High‐resolution fi eld mapping and 741
analysis of the August –October 2016 coseismic s urface faulting (central Italy earthquakes): Slip 742
distribution, parameterization, and co mparison with gl obal earthquakes. Tectonics, 2019 , 38, 417 –439. 743
https://doi.org/10.1029/2018TC005305 744
16. Galadini, F.; Galli, P. Paleoseismology of silent faults in the C entral Apennines (Italy): the Mt. Vet tore and 745
Laga Mt s. Faults. Annals of Geoph ysics, 2003 , 46, n.5, 815 -836, 201 7TC00458 3 746
17. Koopman, A. Detachm ent tectonics in the central Apennines, Italy. Geologica Eltrai ectina, 1983 , 30,1–155. 747
18. Lavecchia, G. Il sovrascorr imento dei Monti Sibillini: Analisi c inematica e stru tturale. Bollettino della 748
Societa Geologica Italiana, 1985 , 104, 161–194 749
19. Bally, A. W.; Bu rbi, L.; Cooper, C.; Ghelardoni, R. Balanced cross -sections and seismic reflection profiles 750
across the central Apenn ines. Memorie della Societa Geologica Italiana, 1986 , 35, 257–310. 751
20. Barchi, M. Inte gration of a s eismic profile wit h surfac e and sub surface geol ogy in a cross -section through 752
the Umbria -Marche Apennines. Bollettino della Societa Geologica Italiana, 1991 , 110 , 469–479 753
21. Calamita, F.; Pizzi, A.; Ro scioni, M. I "fa sci" di faglie recenti ed att ive di m vetto re – m bove e di m castel lo 754
– m cardosa (appen nino umbro -marchigiano). Studi Geologici Camerti 1992 , volume s peciale (1992/1), 755
81-95. 756
22. Coltorti, M.; Consoli, M.; Dramis, F.; Gentili, B.; Pambianchi G. Evoluzione ge omo rfologica delle piane 757
alluvionali delle Marche centro -meridionali Geogr. Fis. Dinam. Q uat., 14 (1) 1991 , pp. 87 -100 758
23. Blumetti, A. M.; Dramis, F.; Mich etti, A. M. Fault -generated mountain fr onts in the central Apennines 759
(Central Italy): Ge omorphological f eatures and seismotectonic im plications. Ea rth Surface Proce sses and 760
Landforms, 1993 , 18(3), 203–223. https://doi.org/10.1002/esp.329018 0304 761
24. Pizzi, A.; Calamita, F.; Coltorti, M.; Pieru ccini, P. Quater nary normal faults, intramont ane basins and 762
seismicity in th e Umbria -Marche -Abruzzi Apenn ine Ridge (Italy): Contribution of neotectonic analysis to 763
seismic hazard assessment. Bollettino Socie tà Geologica Italiana Special Publication, 2002 , 1(January), 764
923–929. 765
25. Brozzetti, F.; Lavecchia , G. Seismicit y and related ext ensional stress field: the cas e of the Norcia seismic 766
zone. Annales Tectonicae, 1994 , 8, 38–57. 767
26. Calamita, F.; Pizzi, A. Recent and a ctive extensional tectonics in the southern Umbro -Marchean Apenni nes 768
(Central Italy). Memorie della Societa Geologica Italian a, 1994 , 48, 541–548 769
27. Cavinato, G. P.; De Celles, P. G. Extensional basins in the tectonically bimodal central Apennines 770
fold-thrust belt, Italy: Response to corner flow above a subd ucting slab in r etrograde motion. Geology, 771
1999, 27(10), 95 5–958. https://do i.org/10 .1130/0091 -7613(1999)027%3C0955:EBITTB%3E2.3.CO;2 772
28. Galadini, F.; Galli, P. Active tectonics in the central Apennines (italy) ; input data for seismic hazard 773
assessment. Natur al Hazards 2000 , 22, 225-270. 774
29. Pierantoni, P.; Deiana, G.; G aldenzi, S. Strat igraphic and structural features of the Sibillini Mountains 775
(Umbria -Marche Apennines, Italy), Italy. Journal of Geosciences , 2013 132(3), 497 –520. 776
doi:10.3301/IJG.2013.08 777
30. Biella, G .; Lavecchia, G. ; Lozei, A.; Pialli, G.; Scar ascia, S. In P rimi risultati di un'inda gine geofisica e 778
interpretazione geologica del piano di s. Scolastica e del piano grande (norcia, pg), I Convegno Annuale 779
G.N.G.T.S., Roma, 1981 ; Roma, I -TECT -UM. 780
31. Villani, F.; Sapia, V.; B accheschi, P.; Civico, R.; Di Giulio, G.; V assallo, M.; Marc hetti, M .; Pantosti , D. 781
Geometry and structure of a fault‐bounded extensional basin by integrating geophysical surveys and 782
seismic anisotropy across the 30 October 2016 Mw 6.5 eart hquake fault (ce ntral Italy ): The pian grande di 783
Castelluccio basin. Tectonics 2019 . 784
32. Chiaraluc e, L., Di Stefano, R.; Tinti, E.; Scognamiglio, L.; Michele, M.; Casarotti, E.; Cattaneo, M.; De Gori, 785
P.; Chiarabba, C.; Monachesi, G.; Lombardi, A.; Valoroso, L.; Latorre, D.; Marzorati, S. The 2016 Central 786
Italy Seismic Sequence: A First Look at the Mai nshocks, Aftershocks, and Source Models. Seismol. Res. Lett . 787
2017 , 88 (3), 757 –771, doi:10.1785/0220160221 788
33. Michele, M.; Di Stefano, R.; Chiaraluce, L.; Cattaneo, M.; De Gori, P. ; Monachesi, G.; Latorre, D.; Marzorati, 789
S.; Valoroso, L.; Ladina, C. et al. The Amatrice 2016 seismic sequence: A preliminary look at the mainshock 790
and aftershocks distribution, Ann. Geophys., 2016 , 59, doi: 10.4401/ag -7227. 791

Appl. Sci. 2020, 10, x FOR PEER REVIEW 27 of 30
34. Lavecchia, G.; Castaldo, R.; d e Nardis, R.; De Novellis, V.; Ferrarini, F.; Pepe, S.; Brozzetti, F.; Solaro, 792
G.; Cirillo, D.; Bonano, M.; Boncio, P.; Casu, F.; De Luca, C.; Lanari, R.; Manunta, M.; Manzo, M.; Pepe, A.; 793
Zinno, I.; Tizzani, P. Ground deformation and sourc e geometry of th e August 24, 2016 Amatrice 794
earthquake (Central Italy) investigated through anal ytical and numerical modeling of DInSAR 795
measurements and structural -geological data. Geophys. Res. Lett . 2016 , 43, 12,389 –12,398, 796
doi:10.1002/2016GL071723 797
35. Pucci, S.; De Martini, P.M.; Civico, R.; Villani, F.; Nappi, R.; Ricci, T.; Azzaro, R.; Brunori, C.A. ; Caciagli, 798
M.; Cinti, F.R. , et al. Coseismic ruptures of the 24 august 2016, Mw 6.0 Amatrice earthquake (central Italy ). 799
Geophysical Research Letters 2017 . 800
36. Open EMERGEO Workin g Group: Villani, F.; Civico, R.; Pucci, S.; Pizzimenti, L.; Nappi, R.; De Mart ini, 801
P.M.; Agosta, F.; Alessio, G.; Alfonsi, L.; Amanti, M.; Amoroso, S.; Aringoli, D.; Auciello, E.; Azzaro, R.; 802
Baize, S. ; Bello, S.; Benedetti, L. ; Bertagni ni, A.; Binda, G .; Bisson, M.; Blumetti, A.M.; Bonadeo, L.; Boncio, 803
P.; Bornemann, P.; Branca, S.; Braun, T.; Brozzetti, F.; Brunori, C.A.; Burrato, P.; Caciagli, M.; Campobasso, 804
C.; Carafa, M.; Cinti, F.R.; Cirillo, D.; Comerci, V.; Cucci, L.; De Ritis, R .; Deiana, G.; D el Carlo, P.; Del Rio, 805
L.; Delorme, A.; Di Manna, P.; Di Naccio, D.; Falconi, L .; Falcucci, E.; Farabollini, P.; Faure Walker, J.P.; 806
Ferrarini, F.; Ferrario, M.F.; Ferry, M.; Feuillet, N.; Fleury, J.; Fracassi, U.; Frigerio, C.; Galluzzo, F .; 807
Gambillara, R .; Gaudiosi, G.; Goodall, H.; Gori, S.; Gregory, L.C.; Guerrieri, L.; Hailemika el, S.; 808
Hollingsworth, J.; Iezzi, F.; Invernizzi, C.; Jablonská, D.; Jacques, E.; Jomard, H.; Kastelic, V.; Klinger, Y.; 809
Lavecchia, G.; Leclerc, F.; Liberi, F.; Lisi, A.; Livio, F.; Lo Sardo, L.; Malet, J.P.; Mariucci, M.T.; Materazzi, 810
M.; Maubant, L.;Mazz arini, F.; McCaffrey, K.J.W.; Michetti, A. M.; Mildon, Z.K.; Montone, P.; Moro, M.; 811
Nave, R.; Odin, M.; Pace, B.; Paggi, S.; Pagliuca, N.; Pambianchi, G.; Pantos ti, D.; Patera, A.; Pérouse, E.; 812
Pezzo, G.; Piccardi, L.; Pierantoni, P.P. Pignone, M.; Pinzi, S.; Pistolesi, E.; Point, J.; Pousse, L.; Pozzi, A.; 813
Proposito, M.; Puglisi, C.; Puliti, I.; Ricci, T.; Ripamonti, L.; Rizza, M.; Roberts, G.P.; Roncoroni, M.; S apia, 814
V.; Saroli , M.; Sciarra, A.; Scotti, O.; Skupinski, G.; Smedile, A.; Soquet, A.; Tarabusi , G.; Tarquini, S.; 815
Terrana, S.; Tesson, J.; Tondi, E.; Valentini, A.; Vallone, R.; Van der Woerd, J.; Vannoli, P.; Venuti, A.; 816
Vittori, E.; Volatili, T.; Wedmor e, L.N.J.; Wilki nson, M.; Zambrano, M. A database of the coseismic effects 817
following the 30 Oct ober 2016 Norcia earthquake in Central Italy . Scientific Data – Nature 2018, 5, Article 818
number: 180049 doi:10.1038/sdata.2018.49 819
37. Open EMERGEO Working Group: Civi co, R.; Pucci, S .; Villani, F.; Pizzimenti, L.; De Martini, P.M.; Nappi, 820
R.; Agosta, F.; Alessi o, G.; Alfonsi, L.; Amanti, M.; Amoroso, S.; Aringoli, D.; Auciello, E.; Azzaro, R.; 821
Baize, S.; Bello, S.; Benedetti, L.; Bertagnini, A.; Binda, G.; Bisson, M.; Blumetti, A.M.; Bonadeo, L.; Boncio, 822
P.; Bornemann, P.; Branca, S.; Braun, T.; Brozzetti, F.; B runori, C.A.; Buttinelli, M.; Caciagli, M.; 823
Campobasso, C.; Carafa, M.; Cinti, F.R.; Cirillo, D.; Comerci, V.; Cucci, L.; De Ritis, R.; Deiana, G.; Del 824
Carlo, P. ; Burrato, P.; D el Rio, L.; Delorme, A.; Di Manna, P.; Di Naccio, D.; Falconi, L.; Falcucci, E. ; 825
Farabollini, P.; Faure Walker, J.; Ferrarini, F.; Ferrario, M.F.; Ferry, M.; Feuillet, N.; Fleury, J.; Fracassi, U.; 826
Frigerio, C.; Galluzzo, F.; Gambillara, R. ; Gaudiosi, G.; Goodall, H.; Gori, S.; Gregory, L.; Guerrieri, L.; 827
Hailemikael, S.; Iezzi, F.; Invernizzi, C.; Jablonská, D.; Jacques, E.; Jomard, H.; Kastelic, V.; Klinger, Y.; 828
Lavecchia, G.; Leclerc, F.; Liberi, F.; Lisi, A.; Livio, F.; Lo Sardo, L.; Mal et, J.P.; Mariuc ci, M.T.; Materazzi, 829
M.; Mazzarini, F.; McCaffrey, K.; Michetti, A.; Mildon, Z. ; Montone, P.; Moro, M.; Nave, R.; Odin, M.; Pace, 830
B.; Paggi, S.; Pagliuca, N.; Pambianchi, G.; Pantosti, D.; Patera, A.; Pérouse, E.; Pezzo, G.; Piccardi, L.; 831
Pierantoni, P.P.; Pignone, M.; Pinzi, S.; Pistolesi, E.; Point, J.; Pozzi, A.; Proposito, M.; Pu glisi, C.; Puliti, I.; 832
Ricci, T.; Ripamonti, L.; Rizza, M.; Roberts, G.; Roncoroni, M.; Sapia, V.; Saroli, M.; Sciarra, A.; Scotti, O.; 833
Skupinski, G.; Smedile, A .; Tarabusi, G.; Tarquini, S.; Terrana, S.; Tesson, J.; Tiberti, M.M.; Tondi, E.; 834
Valentini, A. ; Vallone, R.; Van der Woerd, J.; Vannoli, P.; Venuti, A.; Vittori, E.; Volatili, T.; Wedmore, L.; 835
Wilkinson, M.; Zambrano, M. Surface ruptures following the 30 October 2016 Mw 6.5 Norcia earthquake; 836
central Italy . Journal of Maps; 2018 , 14 – Issue 2, 151 -160; DOI:10.1080/17445647.2018.1441756 837
38. Livio, F.; Michetti, A.M.; Vittori, E.; Gregory, L.; Wedmore, L.; Piccardi, L.; Tondi, E.; Roberts, G. Central 838
Italy Earth quake Working Gr oup Surface faulting during the August 24, 2016, central Italy earthquake 839
(Mw 6 .0): preliminary results Ann. Geophys., 59, 2016 , pp. 1 -7, 10.4401/ag -7197 Fast Track 5 840
39. Pizzi, A.; Di Domenica, A.; Gallovič, F.; Luzi, L.; Puglia, R. Fault segm entation as cons traint to the 841
occurrence of the mainshocks of the 2016 central Italy seismic se quence. Tectonics 2017 , 36, 2370 -2387. 842
40. Pucci, S.; De Martini, P.M.; Civico, R.; Villani, F.; Nappi, R.; Ricci, T.; Azzaro, R.; Brunori, C.A.; Caciagli, 843
M.; Cinti , F.R. , et al. Coseismic ruptures of the 24 august 2016, Mw 6.0 Amatrice earthquake (central Italy). 844
Geophysical Research Letters 2017 . 845

Appl. Sci. 2020, 10, x FOR PEER REVIEW 28 of 30
41. Iezzi, F.; Mildon , Z.; Walker, J.F.; Roberts, G.; Goodall, H.; Wilkinson, M.; Robertson, J. Coseismic throw 846
variation a cross along -strike bends on active normal faults: Implications for displacement versus length 847
scaling of earthquake ruptures. Journal of Geophysical Resea rch: Solid Earth 2018 , 123, 9817 -9841. 848
42. Galadini, F.; Galli, P. Paleoseismology of silent faults in the central Apennin es (Italy): the Mt. Vettore and 849
Laga Mts. Faults, Annals of Geophysics, 2003 , 46, 815 -836. 850
43. Fieldmove user guide Midland Valley -Petroleum Experts. Available online (February 11, 2020) 851
https://www.petex.com/media/2578/fieldmove_user_guide.pdf 852
44. Dewez, T. J. B.; Gir ardeau -Montaut, D.; A llanic, C.; Rohmer, J. Facets: a cloudcompare plugin to extract 853
geological planes from unstructured 3d point clouds, Int. Arch. Photogramm. Remote Sens. Spa tial Inf. 854
Sci., 2016 , xli-b5, 799 -804, doi:10.5194/isprs -archives -XLI-B5-799-2016. 855
45. Manighetti, I. Ev idence for self -similar, triangular slip distributions on earthquakes: Implications for 856
earthquake and fault mechanics. Journal of Geophysic al Research 2005 , 110. 857
46. Cappa, F.; Perrin, C.; Manighetti, I.; Delor, E. Off -fault long -term dam age: A condition to a ccount for 858
generic, triangular earthquake slip profiles, Geochem. Geophys. Geosyst., 2014 15, 1476 –1493, 859
doi:10.1002/2013GC005182. 860
47. Tao, Z.; Alves, T.M. Impa cts of data sampling on the interpretation of normal fault propagation and 861
segm ent linkage. Tectonop hysics 2019 , 762, 79-96. 862
48. Iezzi, F.; Roberts, G.; Walker, J.F.; Papanikolaou, I. Occurrence of partial and total coseismic ruptures of 863
segmen ted normal fault systems: Insights from the central Apennines , Italy . Journal of Structural Geo logy 864
2019 , 126, 83-99. 865
49. Galli, P.; Castenetto, S.; Peronace, E. The macroseismic intensity distribution of the 30 October 2016 866
earthquake in central Italy (Mw 6.6 ): Seismotectoni c implications. Tectonics , 2017 , 36, 2179 –2191. 867
https://doi .org/10.1002/ 868
50. Galli, P.; Galderisi, A.; Peronace, E.; Giaccio, B.; Hajdas, I.; Messina, P.; Polpetta, F. Quante volte figliola? 869
Confessioni Sibilline di una giovane faglia. In riassunti estesi della comunicazione, 36° convegno 870
nazional e Gruppo Nazionale di Geofisica della Terra Solida, Trieste, 14 -16 November 2017 sessioni 1.1, 871
41-45, volume ISBN 978 -88-940442 -5-6, raccolta ISBN 978 -88-940442 -4-9 872
http://www3. ogs.trieste.it/gngts/files/2017/S11/Riassunti/Galli2.pdf 873
51. Bignami, C.; Valerio, E.; Carminati, E.; Do glioni, C.; Tizzani, P.; Lanari, R. Volume unbalance on the 2016 874
Amatrice – Norcia (central italy) seismic sequence and insights on normal f ault earthquake mechanism. 875
Scientific reports 2019 , 9, 4250. 876
52. Brozzetti, F.; Mondini, A.C.; Pauselli, C.; Mancinelli, P.; Cirillo, D.; Guzzetti, F.; Lavecchia, G. Mainshock 877
Anticipated by Intra -Sequence Ground Deformations: Insi ghts from Multiscale Field and SAR 878
Interferometric Measureme nts. Geosciences 2020, 10(5), 186 https://doi.org/10.3390/geosciences10050186 . 879
53. Cheloni, D.; De Novellis, V.; Alba no, M.; Antonioli, A.; Anzidei, M.; Atzori, S.; Avallone, A.; Bignami, C.; 880
Bonano, M.; Calcaterra, S. , et al. Geodetic model of the 2016 central Italy earthquake sequence inferr ed 881
from insar and gps data. Geophysical Resea rch Letters 2017 , 44, 6778 -6787. 882
54. De Guidi, G.; Vecchio, A.; Brighenti, F.; Caputo, R.; Carnemolla, F.; Di Pietro, A.; Lupo, M.; Maggini, M.; 883
Marchese, S.; Messina, D. , et al. Brief communication co-seismic displ acement on October 26 and 30, 2016 884
(Mw 5.9 an d 6.5) – earthquakes in central Italy from the analysis of a local GNSS network. Natural Hazards 885
and Earth System Sciences 2017 , 17, 1885 -1892. 886
55. De Luca, G.; Di Carlo, G.; Tallini, M . A record of changes in the g ran sasso groundwater before, during and 887
after the 2016 Amatrice earthquake, ce ntral Italy . Scientific reports 2018 , 8, 15982. 888
56. Di Naccio D.; Kastelic V.; Carafa M. M. C.; Esposito C.; Milillo P.; Di Lorenzo C. Gravity versus t ectonics: 889
The case of 2016 Ama trice and Norcia (central Italy) earthquakes surface coseismic fractures. Journ al of 890
Geophysical Research: Earth Surface, 2019 , 124, https://doi.org/10.1029/ 2018JF004762. 891
57. Durante, M.G.; Di Sarno, L.; Zimmaro, P.; Stewart, J.P . Damage to ro adway infrastruc ture from 2016 892
central Italy earthquake seque nce. Earthquake Spectra 2018 , 34, 1721 -1737. 893
58. Ercoli, M.; Forte, E.; Porreca, M.; Carbonell, R.; Pauselli, C.; Minelli, G.; Barchi, M. R. Using Seismic 894
Attributes in seismotectonic r esearch: an ap plication to the Norcia Mw = 6.5 earthquake (30th October 895
2016) in Central Italy . Solid Earth 2020 , 11, 329 -348 https://doi.org/10.5194/se -11-329-2020 . 896
59. Ferrario, M.F.; Livio, F. Characterizing the distributed faulting during the 30 October 2016, central Italy 897
earthquake: A refere nce for fault displacement hazard assessment. Tectonics 2018 , 37, 1256 -1273. 898

Appl. Sci. 2020, 10, x FOR PEER REVIEW 29 of 30
60. Galadini, F.; Falcucci, E.; Gori, S.; Zimmaro, P.; Cheloni, D.; Stewart, J.P. Active faulting in source region of 899
2016–2017 central Italy event sequence. Earthquake Spectra 2018 , 34, 1557 -1583. 900
61. Galderisi, A.; Galli, P. Offset component and fault -block motion during the 2016 central Italy earthquake 901
(Mw 6.6, Monte Vettore fault system). Journal of Structural Geology 2020 , 134, 902
https://doi.org/10.1016/j.jsg.2020.104014 903
62. Galli, P.; Galderisi, A.; Peronace, E.; Giaccio, B.; Hajdas, I.; Messina, P.; Pileggi, D.; Polpetta, F. The 904
awakening of t he dormant mount Vettore fault (2016 central Italy earthquake, Mw 6.6): Paleoseismic clues 905
on its millennial silences. Tectonics 2019 , 38, 687 -705. 906
63. Gentili, S.; Di Giovambattista, R.; Peresan, A. Seismic quiescence preceding the 2016 central italy 907
earthqua kes. Physics of the Earth and Planetary Interiors 2017 , 272, 27-33. 908
64. Huang, M. -H.; Fielding, E.J.; Liang, C.; Milillo, P.; Bekaert, D.; Dreger, D.; Salzer, J. Coseismic deformation 909
and triggered landslides of the 2016 Mw 6.2 Amatrice earthquake in italy. Geophysical Research Letter s 2017 , 910
44, 1266 -1274. 911
65. Liu, C.; Zheng, Y.; Xie, Z.; Xiong, X. Rupture features of the 2016 mw 6.2 Norcia earthquake and its 912
possible relations hip with strong seismic hazards. Geophysical Research Letters 2017 , 44, 1320 -1328. 913
66. Masi, A.; Chiauzzi, L.; Santars iero, G.; Manfredi, V.; Biondi, S.; Spacone, E.; Del Gaudio, C.; Ricci, P.; 914
Manfredi, G.; Verderame, G.M. Seismic response of rc buildings dur ing the Mw 6.0 august 24, 2016 central 915
Italy earthquake: The Amatrice case study. Bulletin of Earthquake Engineeri ng 2017 . 916
67. Mazzoni, S.; Castori, G.; Galasso, C.; Calvi, P.; Dreyer, R.; Fischer, E.; Fulco, A.; Sorrentino, L.; Wilson, J.; 917
Penna, A. , et al. 2016–2017 central Italy earthquake sequence: Seismic retrofit policy and effectiveness. 918
Earthquake Spectra 2018 , 34, 1671 -1691. 919
68. Mildon, Z.K.; Roberts, G.P.; Faure Walker, J.P.; Iezzi, F. Coulomb stress transfer and fault interaction over 920
millennia on non -planar active normal faults: The Mw 6.5–5.0 seismic sequence of 2016 –2017, central italy. 921
Geophysical Journal Intern ational 2017 , 210, 1206 -1218. 922
69. Papadopoulos, G.A.; Ganas, A.; Agalos, A.; Papageorgiou, A.; Triantafyllou, I.; Kontoes , C.; Papoutsis, I.; 923
Diakogianni, G. Earthquake triggering inferred from rupture histories, DINSAR ground deformation and 924
stress -transfer m odelling: The case of central Italy during august 2016 –January 2017. Pure and Applied 925
Geophysics 2017 , 174, 3689 -3711 . 926
70. Picozzi, M.; Bindi, D.; Brondi, P.; Di Giacomo, D.; Parolai, S.; Zollo, A. Rapid determination of p 927
wave -based energy magnitude: Insights on source parameter scaling of the 2016 central Italy earthquake 928
sequence. Geophysical Research Letters 2017 , 44, 4036-4045 929
71. Polcari, M.; Montuori, A.; Bignami, C.; Moro, M.; Stramondo, S.; Tolomei, C. Using multi -band insar data 930
for detecting local deform ation phenomena induced by the 2016 –2017 central Italy seismic sequence. 931
Remote Sensing of Environment 2017 , 201, 234-242. 932
72. Porreca, M.; Minelli, G.; Ercoli, M.; Brobia, A.; Mancinelli, P.; Cruciani, F.; Giorgetti, C.; Carboni, F.; 933
Mirabella, F.; Cavinato, G., et al. Seismic reflection profiles and subsurface geology of the area interested 934
by the 2016 -2017 earthquake sequence (central Italy ). Tectonics 2018 , 37, 1116 -1137. 935
73. Ren, Y.; Wang, H.; Wen, R. Imprint of rupture directivity from ground motions of the 24 august 2016 Mw 936
6.2 central Italy earthquake. Tectonics 2017 , 36, 3178 -3191. 937
74. Scognamiglio, L.; Tinti, E.; Casa rotti, E.; Pucci, S.; Villani, F.; Cocco, M.; Magnoni, F.; Michelini, A.; Dreger, 938
D. Complex fault geometry and rupture dynamics of the Mw 6.5, 30 October 2016, central Italy 939
earthquake. Journal of Geophysical Research: Solid Earth 2018 , 123, 2943 -2964. 940
75. Sextos, A.; De Risi, R.; Pagliaroli, A.; Foti, S.; Passeri, F.; Ausilio, E.; Cairo, R.; Capatti, M.C.; Chiabrando, 941
F.; Chiaradonna, A. , et al. Local site effects and incremental damage of buildings during the 2016 central 942
Italy earthquake sequence. Earthqua ke Spectra 2018 , 34, 1639 -1669. 943
76. Smeraglia, L.; Billi, A.; Carminati, E.; Cavallo, A.; Doglioni, C. Field – to nano -scale evidence for weakenin g 944
mechanisms along the fault of the 2016 Amatrice and Norcia earthquakes, Italy . Tectonophysics 2017 , 945
712-713, 156 -169. 946
77. Stewart, J.P.; Zimmaro, P.; Lanzo, G.; Mazzoni, S.; Ausilio, E.; Aversa, S.; Bozzoni, F.; Cairo, R.; Capatti, 947
M.C.; Castiglia, M. , et al. Reconnaissance of 2016 central Italy earthquake sequence. Earthquake Spectra 2018 , 948
34, 1547 -1555. 949
78. Suteanu, C.; Liucci, L.; Melelli, L. The central Italy seismic sequence (2016): Spatial patterns and dynamic 950
fingerprints. Pure and Applied Geophysics 2017, 175, 1-24. 951

Appl. Sci. 2020, 10, x FOR PEER REVIEW 30 of 30
79. Testa, A., Boncio, P., Di Donato, M., Mataloni, G., Brozzetti, F., Cirillo D. Mapping t he geology of the 2016 952
Central Italy earthquake fault (Mt. Vettore – Mt. Bove fault, Sibillini Mts.): geological details on the Cupi – 953
Ussita and Mt. Bove – Mt. Porche segments and overall pattern of coseismic surface faulting. Geological 954
Field Trips and M aps, 2019, https://doi.org/10.3301/GFT.2019.03 955
80. Tinti, E.; Scognamiglio, L.; Michelini, A.; Cocco, M. Slip heterogeneity and directivity of the ml 6.0, 201 6, 956
Amatrice earthquake estimated with rapid finite -fault inversion. Geophysical Research Letters 2016 , 43, 957
10,745 -710,752. 958
81. Tung, S.; Masterlark, T. Delayed poroelastic triggering of the 2016 october visso earthquake by the august 959
Amatrice earthquake, Italy. Geophysical Research Letters 2018 , 45, 2221 -2229. 960
82. Tung, S.; Masterlark, T. Resolving source geomet ry of the 24 august 2016 Amatrice , central Italy , 961
earthquake from insar data and 3d finite‐element modeling. Bulletin of the Seismological Society of Amer ica 962
2018 , 108, 553 -572. 963
83. Valentini, A.; Pace, B.; Boncio, P.; Visini, F.; Pagliaroli, A.; Pergalani, F . Definition of seismic input from 964
fault‐based PSHA : Remarks after the 2016 central Italy earthquake sequence. Tectonics 2019 , 38, 595 -620. 965
84. Valerio, E.; Tizzani, P.; Carminati, E.; Doglioni, C.; Pepe, S.; Petricca, P.; De Luca, C.; Bignami, C.; Solaro, 966
G.; Castaldo, R. , et al. Ground deformation and source geometry of the 30 October 2016 Mw 6.5 Norcia 967
earthquake (central Italy ) investigated through seismol ogical data, dinsar measurements, and numerical 968
modelling. Remote Sensing 2018 , 10, 1901. 969
85. Walters, R.J.; Gregory, L.C.; Wedmore, L.N.J.; Craig, T.J.; McCaffrey, K.; Wilkinson, M.; Chen, J.; Li, Z.; 970
Elliott, J.R.; Goodall, H. , et al. Dual control of fault intersections on stop -start rupture in the 2016 central 971
Italy seismic sequence. Earth and Pl anetary Science Letters 2018 , 500, 1-14. 972
86. Wang, L.; Gao, H.; Feng, G.; Xu, W. Source parameters and triggering links of the earthquake sequence in 973
central Italy from 2009 to 2016 analyzed with gps and insar data. Tectonophysics 2018 , 744, 285 -295. 974
87. Whitney , R. Approximate recovery of residual displacement from the strong motion recordings of the 24 975
august 2016 Amatrice , Italy earthquake. Bulletin of Earthquake Engine ering 2017 , 16, 1847 -1868. 976
88. Wilkinson, M.W.; McCaffrey, K.J.W.; Jones, R.R.; Roberts, G.P.; Holdsworth, R.E.; Gregory, L.C.; Walters, 977
R.J.; Wedmore, L.; Goodall, H.; Iezzi, F. Near -field fault slip of the 2016 Vettore Mw 6.6 earthquake (central 978
Italy ) meas ured using low -cost GNSS . Scientific reports 2017 , 7, 4612 . 979
89. Xu, G.; Xu, C.; Wen, Y.; Jiang, G. Source parameters of the 2016 –2017 central italy earthquake sequence 980
from the sentinel -1, alos -2 and gps data. Remote Sensing 2017 , 9, 1182. 981
90. Zimmaro, P.; Scass erra, G.; Stewart, J.P.; Kishida, T.; Tropeano, G.; Castiglia, M.; Pelekis , P. Strong ground 982
motion characteristics from 2016 central Italy earthquake sequence. Earthquake Spectra 2018 , 34, 1611 -1637. 983
91. Franke, K.W.; Lingwall, B.N.; Zimmaro, P.; Kayen, R.E.; Tommasi, P.; Chiabrando, F.; Santo, A. Phased 984
reconnaissance approach to documenting landslides following the 2016 central Italy earthquakes. 985
Earthquake Spectra 2018 , 34, 1693 -1719. 986
92. Gori, S.; Falcucci, E.; Galadini, F.; Zimmaro, P.; Pizzi, A.; Kayen, R. E .; Lingwall, B. N.; Moro, M.; Saroli, M.; 987
Fubelli, G.; Di Domenica A. and Stewart J. P.; Surface Faulting Caused by the 2016 Central Italy Seismic 988
Sequence: Field Mapping and LiDAR/UAV Imaging. Earthquake Spectra , 2018, Volume 34, No. 4, pages 989
1585–1610. 990
93. Pavlides, S.; Chatzipetros, A.; Papathanasiou, G.; Georgiadis, G.; Sboras, S.; Valkaniotis, S. Ground 991
deformation and fault modeling of the 2016 sequence (24 Aug . – 30 Oct.) in central Apennines (central 992
Italy ). Bulletin of the Geological Society of Greece 2017 , 51, 76. 993
94. Perouse, E.; Benedetti, L.; Fleury, J.; Rizza, M.; Puliti, I .; Billant, J.; et al. Coseismic slip vectors of 24 August 994
and 30 October 2016 earthquakes in Central Italy: Oblique slip and regional kinematic implications. 995
Tectonics, 2018 , 37. ht tps://doi.org/10.1029/2018TC005083 996
95. Tarquini, S.; Vinci, S.; Favalli, M.; D oumaz, F.; Fornaciai, A.; Nannipieri, L. Release of a 10 -m-resolution 997
DEM for the Italian territory: Comparison with global -coverage DEMs and anaglyph -mode exploration 998
via the web, C omputers & Geosciences , 2012 , 38, 168 -170. doi: doi:10.1016/j.cageo.2011. 04.018 999
96. La carta geologica d'Italia – scala 1: 100.000 – Foglio Geologico n. 132. Norcia 1000
1001
© 20 20 by the authors. Submitted for possible open access publication under the terms
and co nditions of the Creative Commons Attribution (CC BY) license
(http://creativecommons.org/licenses/by/4.0/).
1002