Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest

Dunford, R. W.; Michel, Kristell; Gagnage, M.; Piégay, Hervé; Trémélo, Marie-Laure

doi:10.1080/01431160903023025

Cited by 191 publications

(166 citation statements)

References 35 publications

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“…In a relatively long-term study, Dunford et al (2009) andHervouet et al (2011) explored annual landscape changes after the flood using RPAS-derived images together with other data sets such as satellite image archives or a manned motor paraglider. Their work assessed the progressive development of vegetation on a braided channel at an annual scale, which appears to be controlled by local climate including rainfall, humidity and air temperature, hydrology, groundwater level, topography and seed availability.…”

Section: Post-flood Changesmentioning

confidence: 99%

“…Environmental and geological monitoring can profit from fast multi-temporal acquisitions delivering high-resolution images (Thamm and Judex, 2006;Niethammer et al, 2010). RPASs can also be considered a good solution for mapping and monitoring different active processes at the earth's surface (Fonstad et al, 2013;Piras et al, 2017;Feurer et al, 2017;Hayakawa et al, 2018) such as at glaciers (Immerzeel et al, 2014;Ryan et al, 2015;Fugazza et al, 2017), Antarctic moss beds (Lucieer et al, 2014b), coastal areas (Delacourt et al, 2009;Klemas, 2015), interseismic deformations (Deffontaines et al, 2017(Deffontaines et al, , 2018 and in river morphodynamics (Gomez and Purdie, 2016;Jaud et al, 2016;Aicardi et al, 2017;Bolognesi et al, 2016;Benassai et al, 2017), debris flows (Wen et al, 2011) and river channel vegetation (Dunford et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

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Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Giordan

Hayakawa

Nex

et al. 2018

Nat. Hazards Earth Syst. Sci.

145

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Abstract. The number of scientific studies that consider possible applications of remotely piloted aircraft systems (RPASs) for the management of natural hazards effects and the identification of occurred damages strongly increased in the last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of the literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPASs can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes such as landslides or volcanic activities but can also define the effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazards. IntroductionIn the last three decades, the number of natural disasters showed a positive trend with an increase in the number of affected populations. Disasters not only affected the poor and characteristically more vulnerable countries but also those thought to be better protected. The Annual Disaster Statistical Review describes recent impacts of natural disasters on the population and reports 342 naturally triggered disasters in 2016 (Guha-Sapir et al., 2017). This is less than the annual average disaster frequency observed from 2006 to 2015 (376.4 events). However, natural disasters are still responsible for a high number of casualties (8733 death). In the period 2006-2015, the average number of causalities caused annually by natural disasters is 69 827. In 2016, hydrological disasters (177) had the largest share in natural disaster occurrence (51.8 %), followed by meteorological disasters (96; 28.1 %), climatological disasters (38; 11.1 %) and geophysical disasters (31; 9.1 %) (Guha-Sapir et al., 2017). To face these disasters, one of the most important solutions is the use of systems able to provide an adequate level of information for correctly understanding these events and their evolution. In this context, surveying and monitoring natural hazards gained importance. In particular, during the emergency phase it is very important to evaluate and control the phenomenon of evolution, preferably operating in near real time or real time, and consequently, use this information for a better risk assessment scenario. The available acquired data must be processed rapidly to support the emergency services and decision makers.Recently, the use of remote sensing (satellite and airborne platform) in the field of natural hazards and disasters has become common, also supported by the increase in geospatial technologies and the ability to provide and process up-to-date imagery (Joyce et al., 2009;Tarolli, 2014). Remotely sensed data play an integral role in predicting hazard events such as floods and landslides, subsidence events and other ground instabilities. Because of their acquisition mode and capabilPublished by Copern...

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Section: Post-flood Changesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Giordan

Hayakawa

Nex

et al. 2018

Nat. Hazards Earth Syst. Sci.

145

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“…When a good-quality digital terrain model is available, UAS-derived photogrammetric point clouds (>10 points/m 2 ) can provide a canopy height model (CHM) with a quality comparable to light detection and ranging (LiDAR) CHM but with significant cost differences (Lisein et al 2013b). References on classification of forest species by use of UAS imagery are still rare in the literature and include only the single-date approach (Dunford et al 2009;Gini et al 2014). However, useful pioneering studies are available on vegetation mapping projects based on UAS imagery (Knoth et al 2013;Zaman et al 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Because of its very high spatial resolution (<0.1-m ground sampling distance (GSD)), UAS imagery is regularly characterized as hyperspatial imagery (Carbonneau and Piégay 2012;Greenberg et al 2005;Laliberte et al 2007;Strecha et al 2012). Many studies have taken advantage of these two characteristics, for a broad range of environmental applications, such as landslide mapping (Lucieer et al 2014), forest fire mapping (de Dios et al 2011;Merino et al 2012;Urbahs et al 2013), precision farming (Bendig et al 2013), wildlife census (Lisein et al 2013a;Vermeulen et al 2013), tree and forest characterization (Lisein et al 2013b;Zarco-Tejada et al 2014), forest biodiversity assessment (Getzin et al 2012), and forest species composition (Dunford et al 2009;Gini et al 2014). Recent studies have demonstrated the potential of UAS imagery to finely describe the forest canopy Ellis 2010, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…UAS imagery can be an effective alternative for cost-effectively describing riparian zones at the local scale (Dunford et al 2009;Husson et al 2014). In the ecological scope, the scientific community is very enthusiastic about the use of the UAS, proclaiming the Bdawn of drone ecology^ (Koh and Wich 2012) and that the UAS Bwill revolutionize spatial ecology^ (Anderson and Gaston 2013).…”

Section: Introductionmentioning

confidence: 99%

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Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system

Michez

Piégay

Lisein

et al. 2016

Environ Monit Assess

204

179

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Riparian forests are critically endangered many anthropogenic pressures and natural hazards. The importance of riparian zones has been acknowledged by European Directives, involving multi-scale monitoring. The use of this very-high-resolution and hyperspatial imagery in a multi-temporal approach is an emerging topic. The trend is reinforced by the recent and rapid growth of the use of the unmanned aerial system (UAS), which has prompted the development of innovative methodology. Our study proposes a methodological framework to explore how a set of multi-temporal images acquired during a vegetative period can differentiate some of the deciduous riparian forest species and their health conditions. More specifically, the developed approach intends to identify, through a process of variable selection, which variables derived from UAS imagery and which scale of image analysis are the most relevant to our objectives.The methodological framework is applied to two study sites to describe the riparian forest through two fundamental characteristics: the species composition and the health condition. These characteristics were selected not only because of their use as proxies for the riparian zone ecological integrity but also because of their use for river management.The comparison of various scales of image analysis identified the smallest object-based image analysis (OBIA) objects (ca. 1 m 2 ) as the most relevant scale. Variables derived from spectral information (bands ratios) were identified as the most appropriate, followed by variables related to the vertical structure of the forest. Classification results show good overall accuracies for the species composition of the riparian forest (five classes, 79.5 and 84.1 % for site 1 and site 2). The classification scenario regarding the health condition of the black alders of the site 1 performed the best (90.6 %).The quality of the classification models developed with a UAS-based, cost-effective, and semi-automatic approach competes successfully with those developed using more expensive imagery, such as multi-spectral and hyperspectral airborne imagery. The high overall accuracy results obtained by the classification of the diseased alders open the door to applications dedicated to monitoring of the health conditions of riparian forest. Our methodological framework will allow UAS users to manage large imagery metric datasets derived from those dense time series.

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Application of High‐Resolution Images from Unmanned Aircraft Systems for Watershed and Rangeland Science

Rango

Vivoni

Anderson

et al. 2014

Remote Sensing of the Terrestrial Water Cycle

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Potential and constraints of Unmanned Aerial Vehicle technology for the characterization of Mediterranean riparian forest

Cited by 191 publications

References 35 publications

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Review article: the use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system

Application of High‐Resolution Images from Unmanned Aircraft Systems for Watershed and Rangeland Science

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