Abstract
This article presents a review of the use of unmanned aerial vehicles (UAVs) in the context of geohazards. The pluri-disciplinary role of UAVs is outlined in numerous studies associated with mass earth movements, volcanology, flooding events and earthquakes. Scientific advances and innovations of several research teams around the world are presented from pre-events investigations to crisis management. More particularly, we emphasize the actual status of technology, methodologies and different applications that have emerged with the use of UAVs for each domain. It is shown that the deployment of UAVs in the geohazards context has experienced a tremendous increase during the last 10 years, with the development of more and more miniaturized, flexible and reliable systems. The use of such technology (UAV platform, instrumentation, methodologies) is different for each domain, depending on the spatial extent and the time scale of the observed phenomenon, but also on the practical constraints associated with the civil aviation agencies regulations (outside or within urban areas, before or during a crisis…). This paper also highlights the use of recent methodologies associated with semi-automatic/automatic segmentation or deep learning for the processing of important amounts of data provided by UAVs. Finally, although still sparse, the joint use of UAVs and satellite data is progressing and remains a challenge for future studies in the context of geohazards.
This is a preview of subscription content, log in via an institution to check access.
(Reproduced with the permission of the authors C.Lissak, V. Siccard 2020, Caen University) (Lissak et al. 2019)
(from Turner et al. 2015)
Credit: U.S. Geological Survey
Modified from Feng et al. (2015)
(modified from Bemis et al. 2014)
(modified from Gori et al. 2018)
Similar content being viewed by others
References
Aditian A, Kubota T, Shinohara Y (2018) Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia. Geomorphology 318:101–111. https://doi.org/10.1016/j.geomorph.2018.06.006
Agisoft Metashape (2016) AgiSoft PhotoScan Professional. Version 1.2.6
Agüera-Vega F, Carvajal-Ramírez F, Martínez-Carricondo P (2017a) Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement 98:221–227. https://doi.org/10.1016/j.measurement.2016.12.002
Agüera-Vega F, Carvajal-Ramírez F, Martínez-Carricondo P (2017b) Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry. J Surv Eng. https://doi.org/10.1061/(ASCE)SU.1943-5428.0000206
Akcay O (2015) Landslide fissure inference assessment by ANFIS and logistic regression using UAS-based photogrammetry. ISPRS Int J Geo-Inf 4:2131–2158. https://doi.org/10.3390/ijgi4042131
Angster S, Wesnousky S, Huang W et al (2016) Application of UAV photography to refining the slip rate on the Pyramid Lake Fault Zone, Nevada. Bull Seismol Soc Am 106:785–798. https://doi.org/10.1785/0120150144
Antoine R, Finizola A, Lopez T et al (2017) Electric potential anomaly induced by humid air convection within Piton de La Fournaise volcano, La Réunion Island. Geothermics 65:81–98. https://doi.org/10.1016/j.geothermics.2016.01.003
Antoine R, Tanguy M, Palma Lopes S, Sorin J-L (2019) DIDRO—an innovative multi-sensor UAV system for routine and crisis monitoring of dikes. AGUFM 2019:
Assali P, Grussenmeyer P, Villemin T et al (2014) Surveying and modeling of rock discontinuities by terrestrial laser scanning and photogrammetry: semi-automatic approaches for linear outcrop inspection. J Struct Geol 66:102–114. https://doi.org/10.1016/j.jsg.2014.05.014
Baiocchi V, Dominici D, Mormile M (2013) UAV application in post-seismic environment. Int Arch Photogramm Remote Sens Spat Inf Sci 1:W2
Balek J, Blahůt J (2017) A critical evaluation of the use of an inexpensive camera mounted on a recreational unmanned aerial vehicle as a tool for landslide research. Landslides 14:1217–1224. https://doi.org/10.1007/s10346-016-0782-7
Bally P, Papadopoulou T, Tinel C, Danzeglocke J, Wannop S, Kuklin A (2018) The 17th annual report: international charter space and major disasters, p 72. https://disasterscharter.org/documents/10180/188210/Annual-Report-17.pdf
Bandini F, Butts M, Jacobsen TV, Bauer-Gottwein P (2017) Water level observations from unmanned aerial vehicles for improving estimates of surface water–groundwater interaction. Hydrol Processes 31:4371–4383
Barra A, Monserrat O, Mazzanti P et al (2016) First insights on the potential of Sentinel-1 for landslides detection. Geomat Nat Hazards Risk 7:1874–1883. https://doi.org/10.1080/19475705.2016.1171258
Bato MG, Froger JL, Harris AJL, Villeneuve N (2016) Monitoring an effusive eruption at Piton de la Fournaise using radar and thermal infrared remote sensing data: insights into the October 2010 eruption and its lava flows. Geol Soc Lond Spec Publ 426:533–552. https://doi.org/10.1144/SP426.30
Bemis SP, Micklethwaite S, Turner D et al (2014) Ground-based and UAV-based photogrammetry: a multi-scale, high-resolution mapping tool for structural geology and paleoseismology. J Struct Geol 69:163–178
Berni JAJ, Zarco-Tejada PJ, Suárez L et al (2009) Remote sensing of vegetation from UAV platforms using lightweight multispectral and thermal imaging sensors. Int Arch Photogramm Remote Sens Spat Inf Sci 38:6
Blackett M (2017) An overview of infrared remote sensing of volcanic activity. J Imaging 3:13. https://doi.org/10.3390/jimaging3020013
Blaikie TN, Ailleres L, Betts PG, Cas RAF (2014) Interpreting subsurface volcanic structures using geologically constrained 3-D gravity inversions: examples of maar-diatremes, Newer Volcanics Province, southeastern Australia. J Geophys Res Solid Earth 119:3857–3878. https://doi.org/10.1002/2013JB010751
Bonali FL, Tibaldi A, Marchese F et al (2019) UAV-based surveying in volcano-tectonics: an example from the Iceland rift. J Struct Geol 121:46–64. https://doi.org/10.1016/j.jsg.2019.02.004
Brauneck J, Pohl R, Juepner R (2016) Experiences of using UAVs for monitoring levee breaches. IOP Conf Ser Earth Environ Sci 46:012046. https://doi.org/10.1088/1755-1315/46/1/012046
Brunner D, Lemoine G, Bruzzone L (2010) Earthquake damage assessment of buildings using VHR optical and SAR imagery. IEEE Trans Geosci Remote Sens 48:2403–2420. https://doi.org/10.1109/TGRS.2009.2038274
Bunn M, Leshchinsky B, Olsen M, Booth A (2019) A simplified, object-based framework for efficient landslide inventorying using LIDAR digital elevation model derivatives. Remote Sens 11:303. https://doi.org/10.3390/rs11030303
Calvari S, Neri M, Pinkerton H (2003) Effusion rate estimations during the 1999 summit eruption on Mount Etna, and growth of two distinct lava flow fields. J Volcanol Geotherm Res 119:107–123. https://doi.org/10.1016/S0377-0273(02)00308-6
Caratori Tontini F, Tivey MA, Ronde CEJ, Humphris SE (2019) Heat flow and near-seafloor magnetic anomalies highlight hydrothermal circulation at Brothers Volcano Caldera, Southern Kermadec Arc, New Zealand. Geophys Res Lett 46:8252–8260. https://doi.org/10.1029/2019GL083517
Casagli N, Frodella W, Morelli S et al (2017) Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning. Geoenviron Disasters 4:9. https://doi.org/10.1186/s40677-017-0073-1
Casana J, Kantner J, Wiewel A, Cothren J (2014) Archaeological aerial thermography: a case study at the Chaco-era Blue J community, New Mexico. J Archaeol Sci 45:207–219. https://doi.org/10.1016/j.jas.2014.02.015
Casini G, Hunt DW, Monsen E, Bounaim A (2016) Fracture characterization and modeling from virtual outcrops. AAPG Bull 100:41–61. https://doi.org/10.1306/09141514228
Catalán M, Martos YM, Galindo-Zaldívar J, Funaki M (2014) Monitoring the evolution of Deception Island volcano from magnetic anomaly data (South Shetland Islands, Antarctica). Glob Planet Change 123:199–212. https://doi.org/10.1016/j.gloplacha.2014.07.018
Cawood AJ, Bond CE, Howell JA et al (2017) LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models. J Struct Geol 98:67–82. https://doi.org/10.1016/j.jsg.2017.04.004
Chesley JT, Leier AL, White S, Torres R (2017) Using unmanned aerial vehicles and structure-from-motion photogrammetry to characterize sedimentary outcrops: an example from the Morrison Formation, Utah, USA. Sediment Geol 354:1–8. https://doi.org/10.1016/j.sedgeo.2017.03.013
Chesnel A-L, Binet R, Wald L (2008) Damage assessment on buildings using multisensor multimodal very high resolution images and ancillary data. In: IGARSS 2008—2008 IEEE international geoscience and remote sensing symposium. IEEE, Boston, MA, USA, pp 1252–1255
Cigna F, Banks VJ, Donald AW et al (2017) Mapping ground instability in areas of geotechnical infrastructure using satellite InSAR and Small UAV surveying: a case study in Northern Ireland. Geosciences 7:51. https://doi.org/10.3390/geosciences7030051
Comert R, Avdan U, Gorum T, Nefeslioglu HA (2019) Mapping of shallow landslides with object-based image analysis from unmanned aerial vehicle data. Eng Geol 260:105264. https://doi.org/10.1016/j.enggeo.2019.105264
Cook KL (2017) An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection. Geomorphology 278:195–208. https://doi.org/10.1016/j.geomorph.2016.11.009
Darmawan H, Walter TR, Brotopuspito KS et al (2018) Morphological and structural changes at the Merapi lava dome monitored in 2012–15 using unmanned aerial vehicles (UAVs). J Volcanol Geotherm Res 349:256–267. https://doi.org/10.1016/j.jvolgeores.2017.11.006
De Beni E, Cantarero M, Messina A (2019) UAVs for volcano monitoring: a new approach applied on an active lava flow on Mt. Etna (Italy), during the 27 February–02 March 2017 eruption. J Volcanol Geotherm Res 369:250–262. https://doi.org/10.1016/j.jvolgeores.2018.12.001
de Saint Jean B (2008) Étude et développement d’un système de gravimétrie mobile. Ph.D. thesis, Observatoire de Paris
Deffontaines B, Chang K-J, Champenois J et al (2017) Active interseismic shallow deformation of the Pingting terraces (Longitudinal Valley—Eastern Taiwan) from UAV high-resolution topographic data combined with InSAR time series. Geomat Nat Hazards Risk 8:120–136. https://doi.org/10.1080/19475705.2016.1181678
Delacourt C, Allemand P, Berthier E et al (2007) Remote-sensing techniques for analysing landslide kinematics: a review. Bull Soc Géol France 178:89–100. https://doi.org/10.2113/gssgfbull.178.2.89
Dering GM, Micklethwaite S, Thiele ST et al (2019) Review of drones, photogrammetry and emerging sensor technology for the study of dykes: Best practises and future potential. J Volcanol Geotherm Res 373:148–166. https://doi.org/10.1016/j.jvolgeores.2019.01.018
Derrien A, Villeneuve N, Peltier A, Beauducel F (2015) Retrieving 65 years of volcano summit deformation from multitemporal structure from motion: the case of Piton de la Fournaise (La Réunion Island). Geophys Res Lett 42:6959–6966. https://doi.org/10.1002/2015GL064820
Domeneghetti A, Schumann GJ-P, Tarpanelli A (2019) Preface: remote sensing for flood mapping and monitoring of flood dynamics. Remote Sens 11:943. https://doi.org/10.3390/rs11080943
Duarte D, Nex F, Kerle N, Vosselman G (2018) Multi-resolution feature fusion for image classification of building damages with convolutional neural networks. Remote Sens 10:1636. https://doi.org/10.3390/rs10101636
Edenhofer O, Pichs-Madruga R, Sokona Y et al (2014) Summary for policymakers. In: Climate change 2014: mitigation of climate change. IPCC Working Group III Contribution to AR5. Cambridge University Press
Eker R, Aydın A, Hübl J (2018) Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study. Environ Monit Assess. https://doi.org/10.1007/s10661-017-6402-8
Eltner A, Sardemann H, Grundmann J (2020) Flow velocity and discharge measurement in rivers using terrestrial and unmanned-aerial-vehicle imagery. Hydrol Earth Syst Sci. https://doi.org/10.5194/hess-24-1429-2020
Erdelj M, Natalizio E, Chowdhury KR, Akyildiz IF (2017) Help from the sky: leveraging UAVs for disaster management. IEEE Pervasive Comput 16:24–32. https://doi.org/10.1109/MPRV.2017.11
Everaerts J (2008) The use of unmanned aerial vehicles (UAVs) for remote sensing and mapping. Int Arch Photogramm Remote Sens Sp Inf Sci 37(2008):1187–1192
Fahlstrom P, Gleason T (2012) Introduction to UAV systems. Wiley, Hoboken
Favalli M, Fornaciai A, Nannipieri L et al (2018) UAV-based remote sensing surveys of lava flow fields: a case study from Etna’s 1974 channel-fed lava flows. Bull Volcanol 80:29
Feng Q, Liu J, Gong J (2015) Urban flood mapping based on unmanned aerial vehicle remote sensing and random forest classifier—a case of Yuyao, China. Water 7:1437–1455. https://doi.org/10.3390/w7041437
Fernandez Galarreta J, Kerle N, Gerke M (2015) UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning. Nat Hazards Earth Syst Sci 15:1087–1101. https://doi.org/10.5194/nhess-15-1087-2015
Fernandes O, Murphy R, Adams J, Merrick D (2018) quantitative data analysis: CRASAR small unmanned aerial systems at hurricane Harvey. In: 2018 IEEE international symposium on safety, security, and rescue robotics (SSRR). IEEE, Philadelphia, PA, pp 1–6
Fu G, Liu C, Zhou R et al (2017) Classification for high resolution remote sensing imagery using a fully convolutional network. Remote Sens 9:498. https://doi.org/10.3390/rs9050498
Funaki M, Higashino S-I, Sakanaka S et al (2014) Small unmanned aerial vehicles for aeromagnetic surveys and their flights in the South Shetland Islands, Antarctica. Polar Sci 8:342–356. https://doi.org/10.1016/j.polar.2014.07.001
Gabrlik P (2015) The use of direct georeferencing in aerial photogrammetry with micro UAV. IFAC-PapersOnLine 48:380–385. https://doi.org/10.1016/j.ifacol.2015.07.064
Gailler L, Kauahikaua J (2017) Monitoring the cooling of the 1959 Kīlauea Iki lava lake using surface magnetic measurements. Bull Volcanol. https://doi.org/10.1007/s00445-017-1119-7
Gailler L-S, Lénat J-F, Blakely RJ (2016) Depth to Curie temperature or bottom of the magnetic sources in the volcanic zone of la Réunion hot spot. J Volcanol Geotherm Res 324:169–178. https://doi.org/10.1016/j.jvolgeores.2016.06.005
Gao M, Xu X, Klinger Y et al (2017) High-resolution mapping based on an Unmanned Aerial Vehicle (UAV) to capture paleoseismic offsets along the Altyn-Tagh fault, China. Sci Rep 7:1–11
Gebrehiwot A, Hashemi-Beni L, Thompson G et al (2019) Deep convolutional neural network for flood extent mapping using unmanned aerial vehicles data. Sensors 19:1486. https://doi.org/10.3390/s19071486
Giletycz SJ, Chang C-P, Lin AT-S et al (2017) Improved alignment of the Hengchun Fault (southern Taiwan) based on fieldwork, structure-from-motion, shallow drilling, and levelling data. Tectonophysics 721:435–447. https://doi.org/10.1016/j.tecto.2017.10.018
Giordan D, Hayakawa Y, Nex F et al (2018) The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management. Nat Hazards Earth Syst Sci 18:1079–1096. https://doi.org/10.5194/nhess-18-1079-2018
Giordan D, Adams MS, Aicardi I et al (2020) The use of unmanned aerial vehicles (UAVs) for engineering geology applications. Bull Eng Geol Environ. https://doi.org/10.1007/s10064-020-01766-2
Girardeau-Montaut D, Roux M, Marc R, Thibault G (2005) Change detection on points cloud data acquired with a ground laser scanner. Int Arch Photogramme Remote Sens Spat Inf Sci 36:W19
Gomez C, Kennedy B (2018) Capturing volcanic plumes in 3D with UAV-based photogrammetry at Yasur Volcano—Vanuatu. J Volcanol Geotherm Res 350:84–88. https://doi.org/10.1016/j.jvolgeores.2017.12.007
Gomez C, Purdie H (2016) UAV-based photogrammetry and geocomputing for hazards and disaster risk monitoring—a review. Geoenviron Disasters. https://doi.org/10.1186/s40677-016-0060-y
Gonçalves JA, Henriques R (2015) UAV photogrammetry for topographic monitoring of coastal areas. ISPRS J Photogramm Remote Sens 104:101–111. https://doi.org/10.1016/j.isprsjprs.2015.02.009
Gong J, Wang D, Li Y et al (2010) Earthquake-induced geological hazards detection under hierarchical stripping classification framework in the Beichuan area. Landslides 7:181–189. https://doi.org/10.1007/s10346-010-0201-4
Gonzalez Toro F, Tsourdos A (2018) UAV or drones for remote sensing applications. MDPI Books, Basel
Gori S, Falcucci E, Galadini F et al (2018) Surface faulting caused by the 2016 central Italy seismic sequence: field mapping and LiDAR/UAV imaging. Earthq Spectra 34:1585–1610. https://doi.org/10.1193/111417EQS236MR
Görüm T (2019) Landslide recognition and mapping in a mixed forest environment from airborne LiDAR data. Eng Geol 258:105155. https://doi.org/10.1016/j.enggeo.2019.105155
Graff K, Lissak C, Thiery Y et al (2019) Analysis and quantification of potential consequences in multirisk coastal context at different spatial scales (Normandy, France). Nat Hazards 99:637–664. https://doi.org/10.1007/s11069-019-03763-5
Guilbert V, Antoine R, Heinkele C et al (2020) Fusion of thermal and visible point clouds : application to the Vaches Noires landslide, Normandy, France. In: Accepted for the international archives of the photogrammetry, remote sensing and spatial information sciences (ISPRS Archives). Nice, France, p 6
Harris AJL, Baloga SM (2009) Lava discharge rates from satellite-measured heat flux. Geophys Res Lett. https://doi.org/10.1029/2009GL039717
Harris AJL, Stevenson DS (1997) Thermal observations of degassing open conduits and fumaroles at Stromboli and Vulcano using remotely sensed data. J Volcanol Geotherm Res 76:175–198. https://doi.org/10.1016/S0377-0273(96)00097-2
Harris A, Dehn J, Patrick M et al (2005) Lava effusion rates from hand-held thermal infrared imagery: an example from the June 2003 effusive activity at Stromboli. Bull Volcanol 68:107–117. https://doi.org/10.1007/s00445-005-0425-7
Hastaoğlu KÖ, Gül Y, Poyraz F, Kara BC (2019) Monitoring 3D areal displacements by a new methodology and software using UAV photogrammetry. Int J Appl Earth Obs Geoinf 83:101916. https://doi.org/10.1016/j.jag.2019.101916
Hervo M, Quennehen B, Kristiansen NI et al (2012) Physical and optical properties of 2010 Eyjafjallajökull volcanic eruption aerosol: ground-based, Lidar and airborne measurements in France. Atmos Chem Phys 12:1721–1736. https://doi.org/10.5194/acp-12-1721-2012
Hungr O, Leroueil S, Picarelli L (2014) The Varnes classification of landslide types, an update. Landslides 11:167–194. https://doi.org/10.1007/s10346-013-0436-y
Imam R, Pini M, Marucco G et al (2019) Data from GNSS-based passive radar to support flood monitoring operations. In: 2019 international conference on localization and GNSS (ICL-GNSS). IEEE, Nuremberg, Germany, pp 1–7
Jaboyedoff M, Oppikofer T, Abellán A et al (2012) Use of LIDAR in landslide investigations: a review. Nat Hazards 61:5–28. https://doi.org/10.1007/s11069-010-9634-2
James MR, Robson S, Pinkerton H, Ball M (2006) Oblique photogrammetry with visible and thermal images of active lava flows. Bull Volcanol 69:105–108. https://doi.org/10.1007/s00445-006-0062-9
James MR, Carr B, D’Arcy F et al (2020) Volcanological applications of unoccupied aircraft systems (UAS): developments, strategies, and future challenges. Volcanica 3:67–114
Jiang H, Su Y, Jiao Q et al (2014) Typical geologic disaster surveying in Wenchuan 8.0 earthquake zone using high resolution ground LiDAR and UAV remote sensing. In: Lidar remote sensing for environmental monitoring XIV. International Society for Optics and Photonics, p 926219
Johnson K, Nissen E, Saripalli S et al (2014) Rapid mapping of ultrafine fault zone topography with structure from motion. Geosphere 10:969–986. https://doi.org/10.1130/GES01017.1
Jones RR, Kokkalas S, McCaffrey KJW (2009) Quantitative analysis and visualization of nonplanar fault surfaces using terrestrial laser scanning (LIDAR)—The Arkitsa fault, central Greece, as a case study. Geosphere 5:465–482
Kakooei M, Baleghi Y (2017) Fusion of satellite, aircraft, and UAV data for automatic disaster damage assessment. Int J Remote Sens 38:2511–2534. https://doi.org/10.1080/01431161.2017.1294780
King S, Leon J, Mulcahy M et al (2017) Condition survey of coastal structures using UAV and photogrammetry. Australasian Coasts & Ports 2017: Working with Nature 704
Kitonsa H, Kruglikov SV (2018) Significance of drone technology for achievement of the United Nations sustainable development goals. R-Economy 4(3):115–120. https://doi.org/10.15826/recon.2018.4.3.016
Klemas V (2015) Remote sensing of floods and flood-prone areas: an overview. J Coast Res 31:1005–1013. https://doi.org/10.2112/JCOASTRES-D-14-00160.1
Koutalakis P, Tzoraki O, Zaimes G (2019) UAVs for hydrologic scopes: application of a low-cost UAV to estimate surface water velocity by using three different image-based methods. Drones 3:14. https://doi.org/10.3390/drones3010014
Kreye C, Hein GW, Zimmermann B (2006) Evaluation of airborne vector gravimetry using GNSS and SDINS observations. In: Flury J, Rummel R, Reigber C et al (eds) Observation of the earth system from space. Springer, Berlin, pp 447–461
Labazuy P (2015) Unmaned aerial vehicles (UAVs)-based remote sensing applications for studying and monitoring volcanic environments
Labazuy P, Gouhier M, Harris A et al (2012) Near real-time monitoring of the April-May 2010 Eyjafjallajökull ash cloud: an example of a web-based, satellite data-driven, reporting system. Int J Environ Pollut 48:262. https://doi.org/10.1504/IJEP.2012.049673
Lague D, Brodu N, Leroux J (2013) Accurate 3D comparison of complex topography with terrestrial laser scanner: application to the Rangitikei canyon (N-Z). ISPRS J Photogramm Remote Sens 82:10–26. https://doi.org/10.1016/j.isprsjprs.2013.04.009
Lahousse T, Chang KT, Lin YH (2011) Landslide mapping with multi-scale object-based image analysis—a case study in the Baichi watershed, Taiwan. Nat Hazards Earth Syst Sci 11:2715–2726. https://doi.org/10.5194/nhess-11-2715-2011
Lang S, Füreder P, Rogenhofer E (2018) Earth observation for humanitarian operations. In: Al-Ekabi C, Ferretti S (eds) Yearbook on space policy 2016. Springer, Cham, pp 217–229
Langhammer J, Bernsteinová J, Miřijovský J (2017) Building a high-precision 2D hydrodynamic flood model using UAV photogrammetry and sensor network monitoring. Water 9:861. https://doi.org/10.3390/w9110861
Lee S, Har D, Kum D (2016) Drone-assisted disaster management: finding victims via infrared camera and lidar sensor fusion. In: 2016 3rd Asia-Pacific world congress on computer science and engineering (APWC on CSE), pp 84–89
Leitão JP, Moy de Vitry M, Scheidegger A, Rieckermann J (2016) Assessing the quality of digital elevation models obtained from mini unmanned aerial vehicles for overland flow modelling in urban areas. Hydrol Earth Syst Sci 20:1637–1653. https://doi.org/10.5194/hess-20-1637-2016
Li S, Tang H, He S et al (2015) Unsupervised detection of earthquake-triggered roof-holes from UAV images using joint color and shape features. IEEE Geosci Remote Sens Lett 12:1823–1827. https://doi.org/10.1109/LGRS.2015.2429894
Lin C-Y, Lo H-M, Chou W-C, Lin W-T (2004) Vegetation recovery assessment at the Jou-Jou Mountain landslide area caused by the 921 Earthquake in Central Taiwan. Ecol Model 176:75–81. https://doi.org/10.1016/j.ecolmodel.2003.12.037
Lindner G, Schraml K, Mansberger R, Hübl J (2016) UAV monitoring and documentation of a large landslide. Appl Geomat 8:1–11. https://doi.org/10.1007/s12518-015-0165-0
Lissak C, Gomez C, Shimizu M et al (2019) Drifted wood distribution in Asakura (Kyushu) following the 2017 rain-triggered Debris-flows and Landslides. In: Geophysical research abstracts
Lowe DG (1999) Object recognition from local scale-invariant features. In: Proceedings of the seventh IEEE international conference on computer vision, pp 1150–1157
Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60:91–110. https://doi.org/10.1023/B:VISI.0000029664.99615.94
Lucieer A, de Jong SM, Turner D (2014) Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography. Progress Phys Geogr Earth Environ 38:97–116. https://doi.org/10.1177/0309133313515293
Magee C, Stevenson CTE, Ebmeier SK et al (2018) Magma plumbing systems: a geophysical perspective. J Petrol 59:1217–1251. https://doi.org/10.1093/petrology/egy064
Marshall DM, Barnhart RK, Shappee E, Most MT (2015) Introduction to unmanned aircraft systems. CRC Press, Boca Raton
Mavroulis S, Andreadakis E, Spyrou N-I et al (2019) UAV and GIS based rapid earthquake-induced building damage assessment and methodology for EMS-98 isoseismal map drawing: the June 12, 2017 Mw 6.3 Lesvos (Northeastern Aegean, Greece) earthquake. Int J Disaster Risk Reduct 37:101–169. https://doi.org/10.1016/j.ijdrr.2019.101169
Menegoni N, Meisina C, Perotti C, Crozi M (2018) Analysis by UAV digital photogrammetry of folds and related fractures in the Monte Antola Flysch Formation (Ponte Organasco, Italy). Geosciences 8:299. https://doi.org/10.3390/geosciences8080299
Mezaal M, Pradhan B, Rizeei H (2018) Improving landslide detection from airborne laser scanning data using optimized Dempster–Shafer. Remote Sens 10:1029. https://doi.org/10.3390/rs10071029
Mian O, Lutes J, Lipa G et al (2015) Direct georeferencing on small unmanned aerial platforms for improved reliability and accuracy of mapping without the need for ground control points. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XL-1/W4:397–402. https://doi.org/10.5194/isprsarchives-XL-1-W4-397-2015
Michael N, Shen S, Mohta K et al (2014) Collaborative mapping of an earthquake damaged building via ground and aerial robots. In: Yoshida K, Tadokoro S (eds) Field and service robotics: results of the 8th international conference. Springer, Berlin, pp 33–47
Middlemiss RP, Samarelli A, Paul DJ et al (2016) Measurement of the Earth tides with a MEMS gravimeter. Nature 531:614–617. https://doi.org/10.1038/nature17397
Millington SC, Saunders RW, Francis PN, Webster HN (2012) Simulated volcanic ash imagery: a method to compare NAME ash concentration forecasts with SEVIRI imagery for the Eyjafjallajökull eruption in 2010. J Geophys Res Atmos. https://doi.org/10.1029/2011JD016770
Mokhtar MRM, Matori AN, Yusof KW et al (2014) Assessing UAV landslide mapping using unmanned aerial vehicle (UAV) for landslide mapping activity. Appl Mech Mater 567:669–674. https://doi.org/10.4028/www.scientific.net/AMM.567.669
Moosavi V, Talebi A, Shirmohammadi B (2014) Producing a landslide inventory map using pixel-based and object-oriented approaches optimized by Taguchi method. Geomorphology 204:646–656. https://doi.org/10.1016/j.geomorph.2013.09.012
Mori T, Hashimoto T, Terada A et al (2016) Volcanic plume measurements using a UAV for the 2014 Mt. Ontake eruption. Earth Planets Space 68:49. https://doi.org/10.1186/s40623-016-0418-0
Morsdorf F, Eck C, Zgraggen C et al (2017) UAV-based LiDAR acquisition for the derivation of high-resolution forest and ground information. Lead Edge 36:566–570. https://doi.org/10.1190/tle36070566.1
Murphy R, Dufek J, Sarmiento T et al (2016) Two case studies and gaps analysis of flood assessment for emergency management with small unmanned aerial systems. In: 2016 IEEE international symposium on safety, security, and rescue robotics (SSRR), pp 54–61
Nedjati A, Izbirak G, Vizvari B, Arkat J (2016) Complete coverage path planning for a multi-UAV response system in post-earthquake assessment. Robotics 5:26. https://doi.org/10.3390/robotics5040026
Nex F, Duarte D, Steenbeek A, Kerle N (2019) Towards real-time building damage mapping with low-cost UAV solutions. Remote Sens 11:287. https://doi.org/10.3390/rs11030287
Niethammer U, James MR, Rothmund S et al (2012) UAV-based remote sensing of the Super-Sauze landslide: evaluation and results. Eng Geol 128:2–11. https://doi.org/10.1016/j.enggeo.2011.03.012
Nikolakopoulos K, Kyriou A, Koukouvelas I et al (2019) Combination of aerial, satellite, and UAV photogrammetry for mapping the diachronic coastline evolution: the case of Lefkada Island. ISPRS Int J Geo-Inf 8:489. https://doi.org/10.3390/ijgi8110489
Pajares G (2015) Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs). Photogramm Eng Remote Sens 81:281–330. https://doi.org/10.14358/PERS.81.4.281
Pallister JS, Diefenbach AK, Burton WC et al (2013) The Chaitén rhyolite lava dome: eruption sequence, lava dome volumes, rapid effusion rates and source of the rhyolite magma. Andean Geol. https://doi.org/10.5027/andgeoV40n2-a06
Patrick M, Orr T, Fisher G et al (2017) Thermal mapping of a pāhoehoe lava flow, Kīlauea Volcano. J Volcanol Geotherm Res 332:71–87. https://doi.org/10.1016/j.jvolgeores.2016.12.007
Patrick MR, Younger EF, Tollett W (2019) Lava level and crater geometry data during the 2018 lava lake draining at Kīlauea Volcano, Hawaii. U.S. Geological Survey data release. https://doi.org/10.5066/P9MJY24N
Peltier A, Fontaine FJ, Finizola A et al (2018) Volcano destabilizations: from observations to an integrated model of active deformation. In: AGU fall meeting abstracts, p 23
Perks MT, Russell AJ, Large ARG (2016) Advances in flash flood monitoring using UAVs. Hydrol Earth Syst Sci 20:4005–4015. https://www.hydrol-earth-syst-sci.net/20/4005/2016/doi:10.5194/hess-20-4005-2016
Peternel T, Kumelj Š, Oštir K, Komac M (2017) Monitoring the Potoška planina landslide (NW Slovenia) using UAV photogrammetry and tachymetric measurements. Landslides 14:395–406. https://doi.org/10.1007/s10346-016-0759-6
Petley DN, Crick WD, Hart AB (2002) The use of satellite imagery in landslide studies in high mountain areas. In: Proceedings of the 23rd Asian conference on remote sensing (ACRS 2002), Kathmandu
Picard D, Attoui M, Sellegri K (2019) B3010: a boosted TSI 3010 condensation particle counter for airborne studies. Atmos Measur Tech. https://doi.org/10.5194/amt-12-2531-2019
Piégay H, Arnaud F, Belletti B et al (2020) Remotely sensed rivers in the Anthropocene: state of the art and prospects. Earth Surf Processes Landf 45:157–188. https://doi.org/10.1002/esp.4787
Pieri D, Ma C, Simpson JJ et al (2002) Analyses of in situ airborne volcanic ash from the February 2000 eruption of Hekla Volcano, Iceland. Geophys Res Lett 29:191–194. https://doi.org/10.1029/2001GL013688
Popescu D, Ichim L, Stoican F (2017) Unmanned aerial vehicle systems for remote estimation of flooded areas based on complex image processing. Sensors 17:446. https://doi.org/10.3390/s17030446
Rathje EM, Franke K (2016) Remote sensing for geotechnical earthquake reconnaissance. Soil Dyn Earthq Eng 91:304–316. https://doi.org/10.1016/j.soildyn.2016.09.016
Rau JY, Jhan JP, Lo CF, Lin YS (2012) Landslide mapping using imagery acquired by a fixed-wing UAV. ISPRS Int Arch the Photogramm Remote Sens Spat Inf Sci XXXVIII-1/C22:195–200. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-195-2011
Ridolfi E, Manciola P (2018) Water level measurements from drones: a pilot case study at a dam site. Water 10:297. https://doi.org/10.3390/w10030297
Rinaldi P, Larrabide I, D’Amato JP (2019) Drone based DSM reconstruction for flood simulations in small areas: a pilot study. In: Rocha Á, Adeli H, Reis LP, Costanzo S (eds) New knowledge in information systems and technologies. Springer, Cham, pp 758–764
Rossi G, Nocentini M, Lombardi L et al (2016) Integration of multicopter drone measurements and ground-based data for landslide monitoring. In: Aversa et al. (eds) Landslides and engineered slopes. Experience, theory and practice, Rome, Italy, p 6
Rossi G, Tanteri L, Tofani V et al (2018) Multitemporal UAV surveys for landslide mapping and characterization. Landslides 15:1045–1052. https://doi.org/10.1007/s10346-018-0978-0
Rothmund S, Vouillamoz N, Joswig M (2017) Mapping slow-moving alpine landslides by UAV—opportunities and limitations. Lead Edge 36:571–579. https://doi.org/10.1190/tle36070571.1
Rüdiger J, Tirpitz J-L, de Moor JM et al (2018) Implementation of electrochemical, optical and denuder-based sensors and sampling techniques on UAV for volcanic gas measurements: examples from Masaya, Turrialba and Stromboli volcanoes. Atmos Measur Tech. https://doi.org/10.5194/amt-11-2441-2018
Rupnik E, Daakir M, Pierrot Deseilligny M (2017) MicMac—a free, open-source solution for photogrammetry. Open Geospat Data Softw Stand. https://doi.org/10.1186/s40965-017-0027-2
Saggiani G, Ceruti A, Amici S et al (2006) UAV systems volcano monitoring: first test on Stromboli on October 2004. In: Geophysical research abstracts. Munich, Germany, p 1
Saito H, Korup O, Uchida T et al (2014) Rainfall conditions, typhoon frequency, and contemporary landslide erosion in Japan. Geology 42:999–1002. https://doi.org/10.1130/G35680.1
Sandvik KB, Lohne K (2014) The rise of the humanitarian drone: giving content to an emerging concept. Millennium 43:145–164. https://doi.org/10.1177/0305829814529470
Sanyal J, Lu XX (2004) Application of remote sensing in flood management with special reference to monsoon Asia: a review. Nat Hazards 33:283–301. https://doi.org/10.1023/B:NHAZ.0000037035.65105.95
Sanz-Ablanedo E, Chandler JH, Rodríguez-Pérez JR, Ordóñez C (2018) Accuracy of unmanned aerial vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used. Remote Sens 10:1606. https://doi.org/10.3390/rs10101606
Saroglou C, Asteriou P, Zekkos D et al (2018) UAV-based mapping, back analysis and trajectory modeling of a coseismic rockfall in Lefkada island, Greece. Nat Hazards Earth Syst Sci 18:321–333. https://doi.org/10.5194/nhess-18-321-2018
Scaioni M, Longoni L, Melillo V, Papini M (2014) Remote sensing for landslide investigations: an overview of recent achievements and perspectives. Remote Sens 6:9600–9652. https://doi.org/10.3390/rs6109600
Schneider DJ, Vallance JW, Logan M et al (2005) Airborne thermal infrared imaging of the 2004–2005 eruption of Mount St. Helens. In: AGU fall meeting abstracts 24
Schumann GJ-P, Domeneghetti A (2016) Exploiting the proliferation of current and future satellite observations of rivers. Hydrol Processes 30:2891–2896. https://doi.org/10.1002/hyp.10825
Scott JE, Scott CH (2019) Models for drone delivery of medications and other healthcare items. In: Unmanned aerial vehicles: breakthroughs in research and practice. IGI Global, pp 376–392
Smith LC (1997) Satellite remote sensing of river inundation area, stage, and discharge: a review. Hydrol Processes 11:1427–1439. https://doi.org/10.1002/(SICI)1099-1085(199708)11:10%3c1427:AID-HYP473%3e3.0.CO;2-S
Spampinato L, Calvari S, Oppenheimer C, Boschi E (2011) Volcano surveillance using infrared cameras. Earth-Sci Rev 106:63–91. https://doi.org/10.1016/j.earscirev.2011.01.003
Stumpf A, Kerle N (2011) Combining Random Forests and object-oriented analysis for landslide mapping from very high resolution imagery. Procedia Environ Sci 3:123–129. https://doi.org/10.1016/j.proenv.2011.02.022
Stumpf A, Malet J-P, Kerle N et al (2013) Image-based mapping of surface fissures for the investigation of landslide dynamics. Geomorphology 186:12–27. https://doi.org/10.1016/j.geomorph.2012.12.010
Stumpf A, Malet J-P, Allemand P et al (2015) Ground-based multi-view photogrammetry for the monitoring of landslide deformation and erosion. Geomorphology 231:130–145. https://doi.org/10.1016/j.geomorph.2014.10.039
Sui H, Tu J, Song Z et al (2014) A novel 3D building damage detection method using multiple overlapping UAV images. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XL–7:173–179. https://doi.org/10.5194/isprsarchives-XL-7-173-2014
Tang C, Tanyas H, van Westen CJ et al (2019) Analysing post-earthquake mass movement volume dynamics with multi-source DEMs. Eng Geol 248:89–101. https://doi.org/10.1016/j.enggeo.2018.11.010
Tanteri L, Rossi G, Tofani V et al (2017) Multitemporal UAV survey for mass movement detection and monitoring. In: Mikos M, Tiwari B, Yin Y, Sassa K (eds) Advancing culture of living with landslides. Springer, Cham, pp 153–161
Tauro F, Porfiri M, Grimaldi S (2016) Surface flow measurements from drones. J Hydrol 540:240–245. https://doi.org/10.1016/j.jhydrol.2016.06.012
Techy L, Schmale DG, Woolsey CA (2010) Coordinated aerobiological sampling of a plant pathogen in the lower atmosphere using two autonomous unmanned aerial vehicles. J Field Robot 27:335–343. https://doi.org/10.1002/rob.20335
Terada A, Morita Y, Hashimoto T et al (2018) Water sampling using a drone at Yugama crater lake, Kusatsu-Shirane volcano, Japan. Earth Planets Space. https://doi.org/10.1186/s40623-018-0835-3
Thiebes B, Tomelleri E, Mejia Aguilar A et al (2016) Assessment of the 2006 to 2015 Corvara landslide evolution using a UAV-derived DSM and orthophoto. CRC Press, Boca Raton, pp 1897–1902
Thiele ST, Varley N, James MR (2017) Thermal photogrammetric imaging: A new technique for monitoring dome eruptions. J Volcanol Geotherm Res 337:140–145. https://doi.org/10.1016/j.jvolgeores.2017.03.022
Tofani V, Segoni S, Agostini A et al (2013) Technical note: use of remote sensing for landslide studies in Europe. Natural Hazards Earth Syst Sci 13:299–309. https://doi.org/10.5194/nhess-13-299-2013
Torrero L, Seoli L, Molino A et al (2015) The use of micro-UAV to monitor active landslide scenarios. In: Lollino G, Manconi A, Guzzetti F et al (eds) Engineering geology for society and territory -, vol 5. Springer, Cham, pp 701–704
Tournadre V, Pierrot-Deseilligny M, Faure PH (2014) UAV photogrammetry to monitor dykes-calibration and comparison to terrestrial lidar. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XL-3/W1:143–148. https://doi.org/10.5194/isprsarchives-XL-3-W1-143-2014
Turner D, Lucieer A, Wallace L (2014) Direct georeferencing of ultrahigh-resolution UAV imagery. IEEE Trans Geosci Remote Sens 52:2738–2745. https://doi.org/10.1109/TGRS.2013.2265295
Turner D, Lucieer A, de Jong S (2015) Time series analysis of landslide dynamics using an unmanned aerial vehicle (UAV). Remote Sens 7:1736–1757. https://doi.org/10.3390/rs70201736
Valkaniotis S, Papathanassiou G, Ganas A (2018) Mapping an earthquake-induced landslide based on UAV imagery; case study of the 2015 Okeanos landslide, Lefkada, Greece. Eng Geol 245:141–152. https://doi.org/10.1016/j.enggeo.2018.08.010
Van Den Eeckhaut M, Kerle N, Poesen J, Hervás J (2012) Object-oriented identification of forested landslides with derivatives of single pulse LiDAR data. Geomorphology 173–174:30–42. https://doi.org/10.1016/j.geomorph.2012.05.024
Vetrivel A, Gerke M, Kerle N et al (2018) Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning. ISPRS J Photogramm Remote Sens 140:45–59. https://doi.org/10.1016/j.isprsjprs.2017.03.001
Villa T, Gonzalez F, Miljievic B et al (2016) An overview of small unmanned aerial vehicles for air quality measurements: present applications and future prospectives. Sensors 16:1072. https://doi.org/10.3390/s16071072
Voigt S, Giulio-Tonolo F, Lyons J et al (2016) Global trends in satellite-based emergency mapping. Science 353:247–252. https://doi.org/10.1126/science.aad8728
Vollgger SA, Cruden AR (2016) Mapping folds and fractures in basement and cover rocks using UAV photogrammetry, Cape Liptrap and Cape Paterson, Victoria, Australia. J Struct Geol 85:168–187. https://doi.org/10.1016/j.jsg.2016.02.012
Wallemacq P, Below R, McLean D (2018) UNISDR and CRED report: economic losses, poverty & disasters (1998–2017), Centre for Research on the Epidemiology of Disasters – CRED. https://urldefense.proofpoint.com/v2/url?u=https-3A__www.cred.be_unisdr-2Dand-2Dcred-2Dreport-2Deconomic-2Dlosses-2Dpoverty-2Ddisasters-2D1998-2D2017&d=DwIDaQ&c=vh6FgFnduejNhPPD0fl_yRaSfZy8CWbWnIf4XJhSqx8&r=r2aSgYn6PHMQXXmeBiKsnvfFG9T9U5fmdQ67xEVmgo0&m=ktrJ0pKA6VD69oYCBwKuReprks4SwDgxCLbHGC58tXE&s=nIlLeOALPXPx1QXrUvFduk1NN9dxWEFl_0H4nHiDH4&e=
Walter M, Niethammer U, Rothmund S, Joswig M (2009) Joint analysis of the Super-Sauze (French Alps) mudslide by nanoseismic monitoring and UAV-based remote sensing. Near Surf Geosci 27:8
Walter TR, Jousset P, Allahbakhshi M et al (2020) Underwater and drone based photogrammetry reveals structural control at Geysir geothermal field in Iceland. J Volcanol Geotherm Res 391:106282. https://doi.org/10.1016/j.jvolgeores.2018.01.010
Watts AC, Ambrosia VG, Hinkley EA (2012) Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sens 4:1671–1692. https://doi.org/10.3390/rs4061671
Weintrit B, Bakuła K, Jędryka M et al (2018) Emergency rescue management supported bu UAV remote sensing data. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XLII-3/W4:563–567. https://doi.org/10.5194/isprs-archives-XLII-3-W4-563-2018
Wessels RL, Vaughan RG, Patrick MR, Coombs ML (2013) High-resolution satellite and airborne thermal infrared imaging of precursory unrest and 2009 eruption at Redoubt Volcano, Alaska. J Volcanol Geotherm Res 259:248–269. https://doi.org/10.1016/j.jvolgeores.2012.04.014
Westoby MJ, Brasington J, Glasser NF et al (2012) ‘Structure-from-Motion’ photogrammetry: a low-cost, effective tool for geoscience applications. Geomorphology 179:300–314. https://doi.org/10.1016/j.geomorph.2012.08.021
Wu C (2011) VisualSFM: a visual structure from motion system. http://www.cs.washington.edu/homes/ccwu/vsfm
Wu C (2013) Towards linear-time incremental structure from motion. In: 2013 International conference on 3D vision. IEEE, Seattle, WA, USA, pp 127–134
Xu Z, Wu L, Zhang Z (2018) Use of active learning for earthquake damage mapping from UAV photogrammetric point clouds. Int J Remote Sens 39:5568–5595. https://doi.org/10.1080/01431161.2018.1466083
Yalcin E (2018) Generation of high-resolution digital surface models for urban flood modelling using UAV imagery. In: WIT transactions on ecology and the environment, WIT Press. Lightning Source, UK, Great Britain, pp 357–366
Yamazaki F, Liu W (2016) Remote sensing technologies for post-earthquake damage assessment: a case study on the 2016 Kumamoto earthquake. Philippines, Cebu City
Yang W, Wang M, Shi P (2013) Using MODIS NDVI time series to identify geographic patterns of landslides in vegetated regions. IEEE Geosci Remote Sens Lett 10:707–710. https://doi.org/10.1109/LGRS.2012.2219576
Yu M, Huang Y, Zhou J, Mao L (2017) Modeling of landslide topography based on micro-unmanned aerial vehicle photography and structure-from-motion. Environ Earth Sci. https://doi.org/10.1007/s12665-017-6860-x
Zarco-Tejada PJ, González-Dugo V, Berni JAJ (2012) Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sens Environ 117:322–337. https://doi.org/10.1016/j.rse.2011.10.007
Zekkos D, Clark M, Cowell K, Medwedeff W, Manousakis J, Saroglou H, Tsiambaos G (2017) Satellite and UAV-enabled mapping of landslides caused by the November 17th 2015 Mw 6.5 Lefkada earthquake. In Proc. 19th Int. Conference on soil mechanics and geotechnical engineering, pp. 17–22
Zhang J (2010) Multi-source remote sensing data fusion: status and trends. Int J Image Data Fusion 1:5–24. https://doi.org/10.1080/19479830903561035
Zhou Y (2019) 100% automatic metrology with UAV photogrammetry and embedded GPS and its application in dike monitoring. PhD thesis, Université Paris-Est
Acknowledgements
This paper arose from the International Workshop on “Natural and man-made hazards monitoring by the Earth Observation missions: current status and scientific gaps” held at the International Space Science Institute (ISSI), Bern, Switzerland, on April 15-18, 2019. The thermal survey of Piton de La Fournaise in 2018 was supported by the SlideVOLC French ANR project. We thank all the authors whose illustrations are presented in this article.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix 1
Bibliographic overview of case studies for mass movements
Appendix 2
Bibliographic overview on developments around sensors mounted on drone and volcanoes case studies.
Appendix 3
Main characteristics of the studies cited on the bibliographic overview on flood monitoring and management using UAVs. Information not provided by the authors in the reviewed studies is marked by the symbol “?”.
Appendix 4
Technical overview of the flights described in Sect. 7 “From tectonophysics studies to post-earthquakes disaster management.”
Rights and permissions
About this article
Cite this article
Antoine, R., Lopez, T., Tanguy, M. et al. Geoscientists in the Sky: Unmanned Aerial Vehicles Responding to Geohazards. Surv Geophys 41, 1285–1321 (2020). https://doi.org/10.1007/s10712-020-09611-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10712-020-09611-7