Geomatics, also known as geospatial technology or
geomatics engineering, refers to the set of disciplines that deal with
gathering, interpreting, processing, modelling, storing and delivering spatial
information. Geomatics, among the others, includes tools and techniques
referable to land surveying and positioning (i.e. topography, Global Navigation
Satellite Systems - GNSS), satellite, aerial and ground-based remote sensing
(i.e. digital photogrammetry, LIght Detection And Ranging - LIDAR, Remotely
Piloted Aircraft System - RPAS), Geographic Information Systems (GIS), digital
mapping and geostatistics.
In recent decades, thanks to technological advances,
these methods have been increasingly spread and used for the study and
management of geological hazard and risk.1-5 This is because they
provide innovative tools in supporting cartographic products and in the
analysis and the quantitative measurement of geological processes located in
inaccessible areas at different scales.6-7 Additionally, Geomatics
provides spatial data for informing decision making processes and ensuring
compliance with regulations.
Recent advances in the information technology industry
have provided the capability to obtain accurate, fully geo-referenced,
three-dimensional datasets that can be used to characterize in detail the
structural and geological setting and the geomorphology of a study area.
Engineering geology applications, as for example the
geo-hydrological risk assessment, the rock fall runout modelling, or the slope
stability analysis, can have a great benefit by the use of remote sensing data
based on satellite platforms, aircrafts and RPAS.8-12 Deterministic
series of data can be interrogated for providing engineering-based solutions to
characterize soils and rock masses, monitor deformation processes, and to add
insight into any underlying failure mechanisms. For example, understanding
characteristics and changes in slope geometry and knowledge of engineering
geological properties of a soil or a rock mass, are essential to reduce risks associated
with slope failure.
Many currently operational missions (i.e. optical,
multispectral, Synthetic Aperture Radar - SAR), as well as ground-based
methodologies (i.e. total station, laser scanning, Infrared - IR thermography)
continue their widespread use, as proved by the increasing number of scientific
papers based on such applications. Recently, mobile terrestrial laser scanning
is also emerging as a remote data collection technique capable of generating
accurate fully three-dimensional virtual models while moving at different
speeds.13-15 Satellite imagery and photos, both from aircraft and
RPAS, can be processed in association with 3D data for producing digital models
to be used in the collection of engineering geological information. Topographic
and geothematic information can be extracted and additional methods developed
for producing spatial data containing numerical records even with a
multi-temporal character.16-19 Geological features of interest can
be spatially located and mapped, as well as information on displacement or
deformation rate in critical sections or regions of a slope provided.20-23
Finally, several benefits can be obtained by
incorporating different geomatic techniques and conventional measurement
devices to provide a comprehensive database required for development of an
effective monitoring and risk management program.24-25 Different techniques, such as high accuracy
discrete point measurement at critical locations or optical fibers along lines
of inspection, can be integrated and used to combine datasets from different
technologies with the aim of complementing missing data resulting from inherent
limitations in one or other technology.26-28
Indeed, often only an integrated approach guarantees
of having valuable and spatially accurate data for subsequent reliable analyses
and associated interpretations.
B, Mansor S, Pirasteh S, Buchroithner MF. Landslide hazard and risk analyses at
a landslide prone catchment area using statistical based geospatial model. Int
J Remote Sens. 2011; 32(14):4075-4087.
M, Oppikofer T, Abellán A, Derron MH, Loye A, Metzger R, Pedrazzini A. Use of
LIDAR in landslide investigations: a review. Nat Hazards. 2012; 61(1):5-28.
A, Monserrat O, Mazzanti P, Esposito C, Crosetto M, Scarascia Mugnozza G. First
insights on the potential of Sentinel-1 for landslides detection. Geomatics,
Natural Hazards and Risk. 2016; (pp. 1-10).
R, Mastrorocco G, Seddaiu M, Rossi D, Vanneschi C. The use of an unmanned
aerial vehicle for fracture mapping within a marble quarry (Carrara, Italy):
photogrammetry and discrete fracture network modelling. Geomatics, Natural
Hazards and Risk. 2016; (pp. 1-19).
S, Atif S, Shafiq, M. GIS based landslide susceptibility mapping of northern
areas of Pakistan, a case study of Shigar and Shyok Basins. Geomatics,
Natural Hazards and Risk. 2016; (pp. 1-19).
S, Tripathi NK, Mansor S, Pradhan B, Ramli MF. Landscapes rendition in Zagros
Mountain, Iran using geoinformation technology. J. Geomatics. 2009; 3:33-39.
R, Francioni M, Riccucci S, Bonciani F, Callegari I. Photogrammetry and laser
scanning for analyzing slope stability and rock fall runout along the
Domodossola–Iselle railway, the Italian Alps. Geomorphology. 2013; 185:110-122.
PK, Tiwari PC, Pant CC. Climate Change accelerating hydrological hazards and
risks in Himalaya: A case study through remote sensing and GIS modeling. International
Journal of Geomatics and Geosciences. 2011; 1(4):678-699.
MA, Sturzenegger M, Stead D, Jaboyedoff M, Lawrence M, Roberts NJ, ... Clague
JJ. Stability analysis of the 2007 Chehalis lake landslide based on long-range
terrestrial photogrammetry and airborne LiDAR data. Landslides. 2012; 9(1):75-91.
10. Akbarimehr M, Motagh M, Haghshenas-Haghighi M. Slope
stability assessment of the sarcheshmeh landslide, Northeast Iran, investigated
using inSAR and GPS observations. Remote Sensing. 2013; 5(8):3681-3700.
11. Francioni M, Salvini R, Stead D, Litrico S. A case
study integrating remote sensing and distinct element analysis to quarry slope
stability assessment in the Monte Altissimo area, Italy. Eng Geol. 2014; 183:290-302.
12. Scaioni M,
Feng T, Barazzetti L, Previtali M, Lu P, Qiao G, ... Li R.
Some applications of 2-D and 3-D photogrammetry during laboratory experiments
for hydrogeological risk assessment. Geomatics, Natural Hazards and Risk,
13. Lato M, Hutchinson J, Diederichs M, Ball D, Harrap R.
Engineering monitoring of rockfall hazards along transportation corridors:
using mobile terrestrial LiDAR. Nat Hazard Earth Sys. 2009; 9(3):935-946.
14. Wang Y, Liang X, Flener C, Kukko A, Kaartinen H,
Kurkela M, ... Alho P. 3D modeling of coarse fluvial sediments based on mobile
laser scanning data. Remote Sensing. 2013; 5(9):4571-4592.
15. Michoud C, Carrea D, Costa S, Derron MH, Jaboyedoff M,
Delacourt C, ... Davidson R. Landslide detection and monitoring capability of
boat-based mobile laser scanning along Dieppe coastal cliffs, Normandy. Landslides.
16. Eltner A, Mulsow C, Maas HG. Quantitative measurement
of soil erosion from TLS and UAV data. ISPRS-International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Sciences. 2013; 1(2):119-124.
17. Gasperini D, Allemand P, Delacourt C, Grandjean P.
Potential and limitation of UAV for monitoring subsidence in municipal
landfills. International Journal of Environmental Technology and Management.
18. Eltner A,
Baumgart P, Maas HG, Faust D. Multi-temporal UAV data for automatic measurement of rill
and interrill erosion on loess soil. Earth Surf Proc Land. 2015; 40(6):741-755.
19. Neugirg F, Stark M, Kaiser A, Vlacilova M, Della Seta M,
Vergari F, ... Haas F.
Erosion processes in calanchi in the Upper Orcia Valley, Southern Tuscany,
Italy based on multitemporal high-resolution terrestrial LiDAR and UAV surveys.
Geomorphology. 2016; 269:8-22.
20. Abellán A,
Vilaplana JM, Calvet J, García-Sellés D, Asensio E. Rockfall monitoring by
Terrestrial Laser Scanning–case study of the basaltic rock face at
Castellfollit de la Roca (Catalonia, Spain). Nat
Hazard Earth Sys. 2011; 11(3):829-841.
21. Salvini R, Vanneschi C, Riccucci S, Francioni M, Gullì
D. Application of an integrated geotechnical and topographic monitoring system
in the Lorano marble quarry (Apuan Alps, Italy). Geomorphology. 2015; 241:209-223.
22. Bar N, Parker R, Thomas SJ. Managing landslide risks
associated with erosion-driven slope instabilities using near real-time
deformation monitoring systems. In Rock Mechanics and Rock Engineering: From
the Past to the Future. 2016; (pp. 1191-1196). CRC Press.
23. Xie M, Huang J, Wang L, Huang J, Wang Z. Early
landslide detection based on D-InSAR technique at the Wudongde hydropower
reservoir. Environmental Earth Sciences. 2016; 75(8):1-13.
24. Rosser NJ,
Petley DN, Lim M, Dunning SA, Allison RJ. Terrestrial laser scanning for
monitoring the process of hard rock coastal cliff erosion. Q J Eng Geol Hydroge.
25. Abellán A, Jaboyedoff M, Oppikofer T, Vilaplana JM.
Detection of millimetric deformation using a terrestrial laser scanner:
experiment and application to a rockfall event. Nat Hazard Earth Sys.
26. Chai J, Wei SM, Chang XT, Liu JX. Monitoring
deformation and damage on rock structures with distributed fiber optical
sensing. Int J Rock Mech Min. 2004; 41:298-303.
27. Wang BJ, Li K, Shi B, Wei GQ. Test on application of
distributed fiber optic sensing technique into soil slope monitoring. Landslides.
28. Zhu HH, Shi B, Zhang J, Yan JF, Zhang CC. Distributed
fiber optic monitoring and stability analysis of a model slope under surcharge
loading. J Mt