Claessens Hugues’s research while affiliated with University of Liège and other places

In 2022, Europe emerged from eight of the hottest years on record, leading to significant spruce mortality across Europe. The particularly dry weather conditions of 2018 triggered an outbreak of bark beetles (Ips typographus), causing the loss of thousands of hectares of Norway spruce stands, including in Wallonia and North-eastern France. A methodology for detecting the health status of spruce was developed based on a dense time series of satellite imagery (Sentinel-2). The time series of satellite images allowed the modelling of the spectral response of healthy spruce forests over the seasons: a decrease in photosynthetic activity of the forest canopy causes deviations from this normal seasonal vegetation index trajectory. These anomalies are caused by a bark beetle attack and are detected automatically. The method leads in the production of an annual spruce health map of Wallonia and Grand-Est. The goal of this paper is to assess the damage caused by bark beetle using the resulting spruce health maps. A second objective was to compare the influence of basic variables on the mortality of spruce trees in these two regions. Lasted 6 years (2017–2022), bark beetle has destroyed 12.2% (23,674 ha) of the spruce area in Wallonia and Grand-Est of France. This study area is composed of three bioclimatic areas: Plains, Ardennes and Vosges, which have not been equally affected by bark beetle attacks. The plains were the most affected, with 50% of spruce forests destroyed, followed by the Ardennes, which lost 11.3% of its spruce stands. The Vosges was the least affected bioclimatic area, with 5.6% of spruce stands lost. For the most problematic sites, Norway spruce forestry should no longer be considered.

The proper choice of the tree species to be grown in a specific forest site requires a good knowledge of the tree species autecology and a comprehensive description of the local environmental conditions. In Belgium (Western Europe), ecological forest site are classified according to three major gradients: climate, soil nutrient (fertility) and soil moisture regimes. Understory indicator species are used by practitioners to determine nutrient and moisture regimes, but requires a significant expertise of forest ecosystems. The present work aims in a first instance at modelling the nutrient and moisture regimes based on species composition. Secondly, a practical decision support tool is developped and made available in order to predict forest nutrient and moisture regime starting from a floristic relevé. To do so, we collected floristic relevés representing understory vegetation diversity in Belgium and covering all the nutrient and moisture gradient. The combination of soil and topographic measurements with the indicator plants presence/absence support forest scientists in inferring a nutrient and moisture regime to each relevé. The resulting dataset was balanced along the different nutrient or moisture regimes and Random Forest classification models were trained in order to predict the forest site characteristic from indicator species presence (or absence). One model was fitted for the prediction of the nutrient regime, exclusively based on the floristic information. A second one was trained to classify the moisture regime. Accurate predictions confirms the appropriate use of indicator species for the Belgian forest site classification. The two models are intregrated in a web application dedicated to forest practionners. This website enables the automatic determination of nutrient and moisture regimes from the species list of a floristic relevé.

Ce guide concerne la gestion de toute végétation ligneuse présente sur les berges et les rives des cours d’eau, qui a une influence directe sur le cours d’eau ou qui est directement influencée par celui-ci. Il a été réalisé par la faculté de Gembloux- Agro-Bio Tech de l’Université de Liège à la demande de la Direction des Cours d’eau non navigables (DCENN, SPW Agriculture, Ressources naturelles et Environnement) du Service Public de Wallonie, en charge de la gestion des cours d’eau non navigables de 1ère catégorie. Il fait suite à de nombreuses collaborations entre l’université et cette administration. Il s’adresse : • aux gestionnaires de cours d’eau (DCENN, Services Techniques Provinciaux, communes, wateringues, SPW Mobilité et Infrastructures) ou du milieu naturel (DNF) ; • aux associations et entreprises dont les activités sont en lien avec les cours d’eau ou le milieu naturel ; • aux propriétaires riverains ; • ou encore à toute personne amenée à s’intéresser à l’arbre en bordure de cours d’eau ou plus globalement dans son lit majeur. Il participe à l’objectif d’une gestion intégrée, équilibrée et durable des ripisylves avec la collaboration de toutes les parties concernées. Ce nouveau guide, qui met à jour et remplace une première version éditée en 2010*, vise à intégrer : • l’évolution du cadre juridique et administratif, et la méthodologie des PARIS (Programmes d’Actions sur les Rivières par une approche Intégrée et Sectorisée) ; • les nouvelles connaissances relatives aux forêts riveraines ; • une couverture plus large des problématiques de gestion. Ce guide s’articule en trois parties. Les deux premières présentent quelques éléments fondamentaux relatifs aux ripisylves et aux spécificités du contexte wallon. La troisième partie est consacrée à des recommandations de gestion sous forme de fiches techniques. Les modalités de gestion proposées dans cet ouvrage sont consensuelles et s’appliquent à des cas idéalisés, typiques des principales problématiques de gestion. Cependant, en matière de cours d’eau, les cas généraux font plutôt figure d’exception, aussi il convient d’adapter la gestion à chaque situation particulière. Ce guide a l’ambition d’apporter l’information nécessaire à cette démarche. Des sources d’information complémentaires sont proposées sous le sigle (+).

D’une invention initialement militaire, les drones - et les applications qui dérivent de leurs utilisation - tendent à se banaliser au sein du domaine civil. En terme d’applications géographiques, les micro-drones (< 2 kg) occupent un segment nouveau dans les techniques d’acquisition d’informations, à mi-chemin entre deux segments plus classiques, représentés par les techniques d’acquisitions « terrain » (LiDAR terrestre, lever topographique, cartographie GPS, ..) et l’imagerie aérienne (caméra métrique, LiDAR aérien, imagerie satellitale). A l’aide d’un micro-drone X100 (Gatewing-Trimble), l’Unité GRFMN a effectué différents survols du projet de restauration du ruisseau du Morby, entrepris dans le cadre du projet Life+ Walphy. Les survols ont permis la réalisation d’orthomosaïques et de MNS (à l’aide d’Agisoft Photoscan) aux différentes étapes du chantier. Une évaluation de la qualité des MNS photogrammétriques générés est réalisée sur base de données LiDAR aérien disponible sur la zone. Une comparaison des coûts sera également réalisée entre les différentes techniques d’acquisition de données topographiques déployées sur le site lors du projet : MNS photogrammétriques UAV et caméra large format, LiDAR aérien.

Introduction : Despite their relatively low area coverage, riparian forests are central landscape features providing several ecosystem services. Nevertheless, they are critically endangered in European countries by human pressures (livestock grazing, land use conflicts, canalizations, waste water, ...) andalso by natural hazards such as the recent black alder (Alnus glutinosa) extensive decline caused by Phytophthora alni. In this study UAV is used to improve the characterization of riparian areas. Riparian forest species are identified at the individual tree level. The health condition of black alder is assessed. For this purpose a computer based approach has been developped, with low needs of specific operator ability or training. Methods : We used the Gatewing X100 to acquire 16 aerial photographs datasets (7 in classic RGB and 9 in RG NIR) during 5 days (form Augustus to October 2012). We processed a CHM in ArcGIS by combining a national Digital Terrain Model with a photogrammetric DSM generated from a single flight photographs dataset with the ”MicMac” opensource platform. The 16 orthophotos were computed with Agisoft Photoscan. Based on the CHM and some basic vegetation index (mean NDVI), a classification/segmentation process was developped in eCognition allowing tree crown extraction. An amount of 113 metrics were computed in eCognition for every tree crown object. The metrics were both derived from the CHM raster and spectral information. Metrics were computed by band (object spectral mean and CHM mean, Harralick entropy, Skewness) but also with band combination (Green NDVI and NDVI). A reference dataset was also acquired through a field survey of 624 individual tree positions accurately localized. The health condition of the black alder was recorded during the field survey. A supervised classification algorithm was developed in R (Random Forest package). Results : Several classification trees were assessed trough global accuracy using the Out Of Bag (OOB) error. The best global accuracy (82%) was obtained when distinguishing the black alder (with no regards for health condition during field survey) from the rest of riparian forest objects. The global accuracy tended to decline when other species were added. When separating healthy black alders from those with symptoms, the global accuracy is 77%. Conclusions : Our study highlights the potential of UAV-based multitemporal orthophotos to identify riparian forest species and health conditions at the tree level. Future studies will focus on quick radiometrics corrections. This could improve global accuracy by reducing the variability caused by illumination conditions