References of "Michez, Adrien"
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See detailMulti-temporal monitoring of a regional riparian buffer network (>12,000 km) with LiDAR and photogrammetric point clouds
Michez, Adrien ULiege; Piégay, Hervé; Lejeune, Philippe ULiege et al

in Journal of Environmental Management (in press)

Riparian buffers are of major concern for land and water resource managers despite their relatively low spatial coverage. In Europe, this concern has been acknowledged by different environmental ... [more ▼]

Riparian buffers are of major concern for land and water resource managers despite their relatively low spatial coverage. In Europe, this concern has been acknowledged by different environmental directives which recommend multi-scale monitoring (from local to regional scales). Remote sensing methods could be a cost-effective alternative to field-based monitoring, to build replicable “wall-to-wall” monitoring strategies of large river networks and associated riparian buffers. The main goal of our study is to extract and analyze various parameters of the riparian buffers of up to 12,000 km of river in southern Belgium (Wallonia) from three-dimensional (3D) point clouds based on LiDAR and photogrammetric surveys to i) map riparian buffers parameters on different scales, ii) interpret the regional patterns of the riparian buffers and iii) propose new riparian buffer management indicators. We propose different strategies to synthesize and visualize relevant information at different spatial scales ranging from local (<10 km) to regional scale (>12,000 km). Our results showed that the selected parameters had a clear regional pattern. The reaches of Ardenne ecoregion have channels with the highest flow widths and shallowest depths. In contrast, the reaches of the Loam ecoregion have the narrowest and deepest flow channels. Regional variability in channel width and depth is used to locate management units potentially affected by human impact. Riparian forest of the Loam ecoregion is characterized by the lowest longitudinal continuity and mean tree height, underlining significant human disturbance. As the availability of 3D point clouds at the regional scale is constantly growing, our study proposes reproducible methods which can be integrated into regional monitoring by land managers. With LiDAR still being relatively expensive to acquire, the use of photogrammetric point clouds combined with LiDAR data is a cost-effective means to update the characterization of the riparian forest conditions. [less ▲]

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See detailRiparian characterization from remote sensing in a multiple scale perspectives. A few examples
Piégay, Hervé; Michez, Adrien ULiege; Raepple, Bianca et al

Conference (2018, October 18)

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See detailUpscaling winter wheat above-ground biomass measurements using multispectral imagery and 3D data from unmanned aerial vehicle
Michez, Adrien ULiege; Bauwens, Sébastien ULiege; Heinesch, Bernard ULiege et al

Poster (2017, October 20)

Field measurements in the ICOS program are spatially limited whereas the monitored gas fluxes may have a large footprint. Aerial remote sensing has the advantage to monitor large areas. The main goal of ... [more ▼]

Field measurements in the ICOS program are spatially limited whereas the monitored gas fluxes may have a large footprint. Aerial remote sensing has the advantage to monitor large areas. The main goal of our research was to test the potential of unmanned aerial vehicles (UAV) to upscale parameters monitored through the ICOS program. In this study, we specifically focus on above-ground biomass (AGB) monitoring in a winter wheat crop. We used a octocopter drone (X frame type) to acquire a time series over the crop growing season (8 flights from the 14th of February 2017 to the 7th of July 2017) of multispectral imagery covering the ICOS candidate station of Lonzée (Wallonia, Belgium) and the surrounding field crop areas (ca. 0.25 km² per flight). The multispectral camera provides spectral information on the green (550 +/- 50 nm), red (660 +/- 50 nm), near infrared (735 +/- 50 nm) and red-edge (790 +/- 10 nm) wavelengths bands. The UAV also brought an off-the-shelf high resolution (20 Mpx) RGB camera to derive accurate 3D data. We performed a photogrammetric 3D reconstruction of the acquired imagery for every flight survey. The images provided by the RGB sensor (Sony RX100) were used to produce a high spatial resolution Digital Surface Model (0.05 m) and the images acquired by the multispectral sensor were used to derive reflectance maps (0.1 m) in the four wavelengths bands. The four reflectance layers were combined to produce two straight-forward vegetation indices (Normalized Difference Vegetation Index and Green NDVI). The photogrammetric DSM’s were combined to a LiDAR Digital Terrain Model (public database, survey in winter 2013) to produce Crop Height Models (CHM) of the study area. We used multiple linear regressions modelling in order to predict the AGB of the field crop monitored by the ICOS station of Lonzée with UAV imagery. AGB=a+b*GNDVI+c*NDVI+d *CHM The field crop data were provided by the ICOS program and by field research conducted in experimental field crops close to the flux tower. The field sampling consisted in destructive samples of the crop which were weighted after drying. For each field sample, an associated area was computed based on the outdistance sowing and the number of sampled crops in order to compute an AGB per area unit (t / Ha). Each AGB field estimation was associated to the closest flight date to build a multi date model presenting good performances (r² = 0.85, RMSE = 2.3 t/Ha). We used the same modelling approach to adjust a single date model to derive a predicted AGB map for the 7th of July. The performance of the single date model is lower but still highlights the biomass variation within the crop (r² = 0.71, RMSE = 1.9 t/Ha). The predicted AGB map displays a high spatial heterogeneity with some spatial patterns. Locally low AGB values are found along two old pedestrian whereas higher AGB values can be associated to areas which were sprayed twice (in-between two tractor tracks). Our results highlight the potential of UAV multispectral imagery to monitor the AGB variation within the footprint of the flux tower and highlight the need for repeated field sampling with a precise geolocation to improve the matching between the flight and the field surveys. [less ▲]

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See detailLinking Forest Cover to Water Quality: A Multivariate Analysis of Large Monitoring Datasets
Brogna, Delphine; Michez, Adrien ULiege; Jacobs, Sander et al

in Water (2017), 9(3), 176

Forested catchments are generally assumed to provide higher quality water. However, this hypothesis must be validated in various contexts as interactions between multiple land use and land cover (LULC ... [more ▼]

Forested catchments are generally assumed to provide higher quality water. However, this hypothesis must be validated in various contexts as interactions between multiple land use and land cover (LULC) types, ecological variables and water quality variables render this relationship highly complex. This paper applies a straightforward multivariate approach on a typical large monitoring dataset of a highly managed and densely populated area (Wallonia, Belgium; 10-year dataset), quantifying forest cover effects on nine physico-chemical water quality variables. Results show that forest cover explains about one third of the variability of water quality and is positively correlated with higher quality water. When controlling for spatial autocorrelation, forest cover still explains 9% of water quality. Unlike needle-leaved forest cover, broad-leaved forest cover presents an independent effect from ecological variables and explains independently 4.8% of water quality variability while it shares 5.8% with cropland cover. This study demonstrates clear independent effects of forest cover on water quality, and presents a method to tease out independent LULC effects from typical large multivariate monitoring datasets. Further research on explanatory variables, spatial distribution effects and water quality datasets could lead to effective strategies to mitigate pollution and reach legal targets. [less ▲]

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See detailCaractérisation des forêts à l’aide de la technologie lidar
Michez, Adrien ULiege; Bauwens, Sébastien ULiege; Bonnet, Stéphanie ULiege et al

in Baghdadi, Nicolas; Zribi, Mehrez (Eds.) Observation des Surfaces Continentales par Télédétection: Agriculture et Forêt (2016)

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See detailCaractérisation multi-échelle des bandes riveraines des cours d’eau wallons par télédétection active et passive
Michez, Adrien ULiege

Doctoral thesis (2016)

Les bandes riveraines des cours d’eau constituent des milieux d’une richesse exceptionnelle aux multiples facettes, comportant les habitats parmi les plus variés, dynamiques et complexes de la surface ... [more ▼]

Les bandes riveraines des cours d’eau constituent des milieux d’une richesse exceptionnelle aux multiples facettes, comportant les habitats parmi les plus variés, dynamiques et complexes de la surface terrestre. Elles sont au cœur des stratégies des politiques de préservation et de restauration de l’environnement qui impliquent la mise en place de suivis multi-échelles devant être répétés dans le temps. La télédétection peut fournir des informations fines tant sur la végétation qui compose les bandes riveraines que sur la structure et les paramètres physiques de celles-ci. Le présent projet de doctorat est articulé autour de l’évaluation de la télédétection en tant qu’outil pour la gestion des cours d’eau ; tant au niveau local (<20 km de cours d’eau, usage de drone) qu’au niveau de l’ensemble du réseau hydrographique wallon (> 12 000 km de cours d’eau). Au niveau local, les drones civils tendent à émerger comme outils de caractérisation environnementale depuis le début des années 2000. Leurs principales caractéristiques sont relatives à leur résolution spatiale et temporelle, permettant d’obtenir des données très fines (résolution au sol ≤ 10cm) au sein d’une fenêtre temporelle très restreinte. Leur usage a été évalué avec succès afin de localiser les plantes invasives des bandes riveraines et de caractériser la composition spécifique et l’état sanitaire de l’aulne glutineux (Alnus glutinosa) en Ardenne. Des résultats satisfaisants ont été atteints dans le cas de l’étude de la détection des trois principales espèces végétales invasives des bandes riveraines wallonnes : balsamine de l'Himalaya (I. glandulifera), berce du Caucase (H. mantegazzianum) et renouée du Japon (F. sachalinensis et F. japonica et hybrides). Les meilleures précisions globales obtenues sont de 97% pour la berce du Caucase. A l’échelle régionale, l’approche développée est basée sur l’usage de données 3D (LiDAR et photogrammétriques) afin de caractériser les bandes riveraines associées à l’ensemble du réseau hydrographique wallon (> 12 000 km) à partir de 6 paramètres. Ces paramètres sont descriptifs de composantes physiques de l’hydromorphologie mais également de la structure des forêts riveraines. Une évaluation des patrons spatiaux de ces paramètres en lien avec différentes informations (occupation du sol, régions naturelles) a été réalisée. S’appuyant sur différentes techniques d’agrégation permettant des visualisations à l’échelle régionale, les résultats obtenus reflètent la connaissance a priori des cordons rivulaires, notamment le constat négatif relatif à la fonctionnalité des bandes riveraines en région limoneuse. Les principales perspectives d’application au domaine de la gestion des cours d’eau sont relatives au développement d’outils d’aide à la décision pour les gestionnaires. A l’échelle locale, une adaptation des solutions développées pour l’usage des drones est nécessaire tant en matière de plateforme (couverture d’un linéaire plus important) qu’en tant qu’outil d’analyse (simplification des chaînes de traitement). A l’échelle régionale, la construction d’indicateurs de gestion nécessitera un travail spécifique quant à la comparaison de la valeur observée à une valeur référence. [less ▲]

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See detailUse of Unmanned Aerial System to assess wildlife (Sus scrofa) damage to crops (Zea mays)
Michez, Adrien ULiege; Morelle, Kevin; Lehaire, François et al

in Journal of Unmanned Vehicle Systems (2016), 4(4)

Damage caused by ungulates to agricultural areas are difficult to evaluate because the real extent of the damage remains usually poorly described and potentially arising conflicts. Recent advances in ... [more ▼]

Damage caused by ungulates to agricultural areas are difficult to evaluate because the real extent of the damage remains usually poorly described and potentially arising conflicts. Recent advances in unmanned aerial system (UAS) provide new versatile mapping and quantification possibilities in a wide range of applications. We used crop fields (Zea mays) damaged by wild boar (Sus scrofa) and compared the extent of the damage by means of three methods: i) traditional ground-based assessment ii) UAS orthoimages with operator delineation and iii) UAS Crop Height Model with automatic delineation based on height threshold. We showed for the first time that UAS could be applied for assessing damage of ungulates to agriculture. The two methods using UAS imagery provide coherent and satisfactory results and trended to underestimate the damage area when compared to in-use ground-based field expertise. However we suggest that performance of UAS should further be tested in variable conditions in order to assess the broad application of this tool. Our study describes the potential of UAS as a tool for estimating more accurately the damage area and subsequently the compensation costs for wildlife damage. The proposed approach can come in support of local and regional policies for the definitions of compensation for farmers. [less ▲]

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See detailCharacterization of Forests with LiDAR Technology
Michez, Adrien ULiege; Bauwens, Sébastien ULiege; Bonnet, Stéphanie ULiege et al

in Baghdadi, Nicolas; Zribi, Mehrez (Eds.) Land Surface Remote Sensing in Agriculture and Forest (2016)

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See detailApport des nuages de points LiDAR et photogrammétriques pour le monitoring de 12000 km de cours d’eau en Wallonie (Belgique)
Michez, Adrien ULiege; Piégay, Hervé; Desteucq, Olivier et al

Conference (2016, June 10)

Sous l’impulsion de son administration, la Wallonie a entamé un processus de révision complète des modalités de la gestion des cours d’eau, notamment à travers le projet des Programmes d’Actions sur les ... [more ▼]

Sous l’impulsion de son administration, la Wallonie a entamé un processus de révision complète des modalités de la gestion des cours d’eau, notamment à travers le projet des Programmes d’Actions sur les Rivières par une approche Intégrée et Sectorisée (PARIS). Les PARIS ont pour but l'intégration dans le temps et dans l’espace de l’ensemble des mesures de gestion spécifiques au linéaire des cours d'eau en fonction d'enjeux prioritaires identifiés à l’échelle d’unités de gestion homogènes, les secteurs (6185 secteurs de gestion de 2 km de long en moyenne). La mise en place et le suivi de ces plans de gestion impliquent de facto le développement d'outils de suivi efficaces, permettant d'établir les états des lieux pour la planification des actes de gestion et à terme, d'évaluer l'efficacité desdits plans de gestion. Ces opérations doivent se réaliser sur près de 12000 km de cours d’eau et de bandes riveraines associées sur une base objective et commune à l’ensemble des gestionnaires de cours d’eau. Des données fines de télédétection étant disponibles et acquises de manière régulière par l’administration wallonne, des solutions dérivées de ces sources de données permettront de répondre partiellement aux besoins réguliers en information des plans de gestion PARIS pour un budget réduit. Pour atteindre cet objectif, un protocole a été établi sur base de nuages points LiDAR (densité ≈ 1 point « sol » / m²) complétés par des nuages de points photogrammétriques dérivés des images individuelles des couvertures ortho du territoire. Ces données ont été utilisées afin de caractériser la structure spatiale des bandes riveraines associées à l’ensemble du réseau hydrographique wallon (> 12 000 km) à travers 6 paramètres. Ces paramètres peuvent être d’ordre hydromorphologique (hauteur des berges, largeur et sinuosité du lit mineur), ou décrire la structure des forêts riveraines (hauteur moyenne, continuité longitudinale et ombrage du lit mineur). Une évaluation des patrons spatiaux de ces différents paramètres en lien avec les caractéristiques des territoires wallons (occupation du sol, régions naturelles) peut être ainsi réalisée. Différentes formes de visualisations de l’information peuvent ainsi appuyer le processus décisionnel des gestionnaires, de l’échelle locale (secteurs d’une masse d’eau DCE - Directive ‘Cadre-Eau’) à l’échelle régionale (354 masse d’eau DCE). L’acquisition des données sur l’ensemble du territoire wallon (15000 km²) a été sous-traitée à différentes compagnies privées, pour des montants approximatifs de 17 et 10 € / km² respectivement pour la donnée LiDAR et ortho. Une plateforme en ligne a récemment été lancée par la Direction des Cours d’Eau Non-Navigables du Service Public de Wallonie (DCENN) en tant que support du projet de plans de gestion PARIS. Les paramètres extraits dans le cadre de ce projet seront prochainement intégrés au sein de cette plateforme permettant leur visualisation à différentes échelles ainsi que l’encodage des actions par les gestionnaires. [less ▲]

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See detailMapping of riparian invasive species with supervised classification of Unmanned Aerial System (UAS) imagery
Michez, Adrien ULiege; Piégay, Hervé; Lisein, Jonathan ULiege et al

in International Journal of Applied Earth Observation and Geoinformation (2016), 44

Riparian zones are key landscape features, representing the interface between terrestrial and aquatic ecosystems. Although they have been influenced by human activities for centuries, their degradation ... [more ▼]

Riparian zones are key landscape features, representing the interface between terrestrial and aquatic ecosystems. Although they have been influenced by human activities for centuries, their degradation has increased during the 20th century. Concomitant with (or as consequences of) these disturbances, the invasion of exotic species has increased throughout the world’s riparian zones. In our study, we propose a easily reproducible methodological framework to map three riparian invasive taxa using Unmanned Aerial Systems (UAS) imagery: Impatiens glandulifera Royle, Heracleum mantegazzianum Sommier and Levier, and Japanese knotweed (Fallopia sachalinensis (F. Schmidt Petrop.), Fallopia japonica (Houtt.) and hybrids). Based on visible and near-infrared UAS orthophoto, we derived simple spectral and texture image metrics computed at various scales of image segmentation (10,30, 45, 60 using eCognition software). Supervised classification based on the random forests algorithm was used to identify the most relevant variable (or combination of variables) derived from UAS imagery for mapping riparian invasive plant species. The models were built using 20% of the dataset, the rest of the dataset being used as a test set (80%). Except for H. mantegazzianum, the best results in terms of global accuracy were achieved with the finest scale of analysis (segmentation scale parameter = 10). The best values of overall accuracies reached 72%, 68%, and 97% for I. glandulifera, Japanese knotweed, and H. mantegazzianum respectively. In terms of selected metrics, simple spectral metrics (layer mean / camera brightness) were the most used. Our results also confirm the added value of texture metrics (GLCM derivatives) for mapping riparian invasive species. The results obtained for I. glandulifera and Japanese knotweed do not reach sufficient accuracies for operational applications. However, the results achieved for H. mantegazzianum are encouraging. The high accuracies values combined to relatively light model-inputs needed (delineation of a few umbels) make our approach a serious contender as a cost-effective tool to improve the field management of H. mantegazzianum. [less ▲]

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See detailClassification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system
Michez, Adrien ULiege; Piégay, Hervé; Lisein, Jonathan ULiege et al

in Environmental Monitoring and Assessment (2016), 188(3),

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 ... [more ▼]

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 OBIA objects (ca. 1 m²) as the most relevant scale. Variables derived from spectral information (bands ratio's) 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 multispectral 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 metrics datasets derived from those dense time series. [less ▲]

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See detailDiscrimination of deciduous tree species from time series of unmanned aerial system imagery
Lisein, Jonathan ULiege; Michez, Adrien ULiege; Claessens, Hugues ULiege et al

in PLoS ONE (2015), 10(11),

Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial ... [more ▼]

Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial System (UAS) should be used in order to efficiently discriminate deciduous tree species. A time series of high resolution UAS imagery was collected to cover the growing season from leaf flush to leaf fall. Full benefit was taken of the temporal resolution of UAS acquisition, one of the most promising features of small drones. The disparity in forest tree phenology is at the maximum during early spring and late autumn. But the phenology state that optimized the classification result is the one that minimizes the spectral variation within tree species groups and, at the same time, maximizes the phenologic differences between species. Sunlit tree crowns (5 deciduous species groups) were classified using a Random Forest approach for monotemporal, two-date and three-date combinations. The end of leaf flushing was the most efficient single-date time window. Multitemporal datasets definitely improve the overall classification accuracy. But single-date high resolution orthophotomosaics, acquired on optimal time-windows, result in a very good classification accuracy (overall out of bag error of 16%). [less ▲]

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See detailForEstimator
Dedry, Laurent ULiege; De Thier, Olivier ULiege; Perin, Jérôme ULiege et al

Software (2015)

ForEstimator est un plugin (une extension) QGIS qui permet d'estimer la hauteur dominante de peuplements résineux en Wallonie.

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See detailForEstimator : un nouvel outil cartographique pour mieux connaître la forêt wallonne
Dedry, Laurent ULiege; De Thier, Olivier ULiege; Perin, Jérôme ULiege et al

in Forêt-Nature (2015), (135), 40-46

Suite à l’acquisition par le Service public de Wallonie d’une couverture LiDAR de l’ensemble du territoire régional, et à l’établissement d’un modèle numérique de hauteur basé sur cette dernière, Gembloux ... [more ▼]

Suite à l’acquisition par le Service public de Wallonie d’une couverture LiDAR de l’ensemble du territoire régional, et à l’établissement d’un modèle numérique de hauteur basé sur cette dernière, Gembloux Agro-BioTech (GxABt) a mis au point un plugin QGIS, baptisé «ForEstimator», permettant aux gestionnaires et propriétaires forestiers de calculer facilement la hauteur dominante de leurs peuplements d’épicéas et de douglas équiennes. De plus, pour corriger l’ancienneté des données LiDAR, le plugin est couplé à un modèle de prédiction de la croissance de la hauteur dominante. Cette originalité permet d’actualiser l’estimation à une date postérieure à l’acquisition des données LiDAR. Parallèlement, l’équipe de GxABT a pu déterminer l’arbre le plus haut de Wallonie. Il s’agit d’un douglas de 61 mètres de haut au sein d’un peuplement mélangé de douglas et tsuga, planté en 1900, situé à Bouillon. ForEstimator permet aux gestionnaires forestiers de produire facilement des cartes de hauteur dominante, de productivité des peuplements, etc. [less ▲]

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See detailI know what you did last summer - High resolution mapping of wild boar damages with drones
Michez, Adrien ULiege; Morelle, Kevin ULiege; Lehaire, François ULiege et al

Poster (2014, September 01)

Wild boar ability to cause important damages to agricultural lands is not anymore to be demonstrated. These damages often raise conflicts between farmers and hunters due to the associated economic losses ... [more ▼]

Wild boar ability to cause important damages to agricultural lands is not anymore to be demonstrated. These damages often raise conflicts between farmers and hunters due to the associated economic losses. Objective and accurate method for real impact assessment of losses suffered by farmers is thus needed. Currently,in Wallonia damage assessment is performed from the ground by experts, asked to evaluate precisely the area impacted. This task is time and man power consuming. Moreover, damaged areas are often large and consequently, sampling is mandatory and can induce accuracy issues. Recent development of unmanned aerial vehicle (UAV / drone) toghether with lower cost and better accessibility for civil society and scientific community, makes now possible the use of this technology for wildlife researches. Through photogrammetric 3D reconstruction of the field crop, UAV can allow to objectively and precisely measure the area impacted by wild boar damages. In a context of increasing issues caused by wild boar to agriculture, and the need for stakeholders for accurate impact assessment, we tested an innovative approach to estimate more effectively the area impacted by wild boar. [less ▲]

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See detailCharacterization of riparian zones in wallonia (belgium)
Michez, Adrien ULiege; Piégay, Hervé; Lejeune, Philippe et al

Conference (2014, June 16)

The present study proposes an innovative approach to automatically extract riparian zone characteristics in order to assess its quality, from pre-determined river management reaches (1-3 km long) to ... [more ▼]

The present study proposes an innovative approach to automatically extract riparian zone characteristics in order to assess its quality, from pre-determined river management reaches (1-3 km long) to regional scale (ca. 13000 km for 1000 management sectors). The aim of this remotely sensed monitoring is to improve the river and riparian zone management and planning by providing some key information for river managers. This first research is exclusively based on data which are available at the regional scale (170000 square km) to develop automated tools to implement the methodology to the whole Walloon river network (13000 km) before 2015 with an update frequency of 3 years (photogrammetric DSM survey frequency). [less ▲]

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