References of "Tychon, Bernard"
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See detailBatch-processing of AquaCrop plug-in for rainfed maize using satellite derived Fractional Vegetation Cover data
Mohamed Sallah, Abdoul-Hamid ULiege; Tychon, Bernard ULiege; Piccard, Isabelle et al

in Agricultural Water Management (2019), 217(346-355),

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See detailLE PEUPLEMENT BIOLOGIQUE DANS LES ÉCOSYSTÈMES AQUATIQUES FACE AUX POLLUANTS ÉMERGENTS : MENACES ET RISQUES
Sossey Alaoui, Khadija ULiege; Tychon, Bernard ULiege

Scientific conference (2018, October 22)

Le projet DIADeM a organisé le 22 octobre 2018 un séminaire au Campus d'Arlon de l'Université de Liège en Belgique. Le Séminaire est organisé par les acteurs scientifiques de l’Uliège, Campus d’Arlon en ... [more ▼]

Le projet DIADeM a organisé le 22 octobre 2018 un séminaire au Campus d'Arlon de l'Université de Liège en Belgique. Le Séminaire est organisé par les acteurs scientifiques de l’Uliège, Campus d’Arlon en collaboration avec les partenaires du projet DIADEM afin de mettre l’accent sur la menace et le danger que les écosystèmes et la biodiversité encourent face aux polluants émergents. Il vise également à mettre en évidence les outils développés pour améliorer le diagnostic des écosystèmes aquatiques. Les déchets ménagers, les hôpitaux, les animaux d’élevage sont des sources importantes de rejets médicamenteux et peuvent polluer les sols et les eaux. Partiellement éliminés par les stations d’épurations, ces résidus pharmaceutiques se retrouvent sur les sols, dans les eaux superficielles et dans les eaux souterraines. Une fois dans l'environnement, elles peuvent contaminer les organismes vivants et potentiellement les affecter. [less ▲]

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See detailModeling the Main Fungal Diseases of Winter Wheat: Constraints and Possible Solutions
El Jarroudi, Moussa ULiege; kouadio, Louis; Tychon, Bernard ULiege et al

in Advances in Plant Pathology (2018)

The first step in the formulation of disease management strategy for any cropping system is to identify the most important risk factors. This is facilitated by basic epidemiological studies of pathogen ... [more ▼]

The first step in the formulation of disease management strategy for any cropping system is to identify the most important risk factors. This is facilitated by basic epidemiological studies of pathogen life cycles, and an understanding of the way in which weather and cropping factors affect the quantity of initial inoculum and the rate at which the epidemic develops. Weather conditions are important factors in the development of fungal diseases in winter wheat, and constitute the main inputs of the decision support systems used to forecast disease and thus determine the timing for efficacious fungicide application. Crop protection often relies on preventive fungicide applications. Considering the slim cost−revenue ratio for winter wheat and the negative environmental impacts of fungicide overuse, necessity for applying only sprays that are critical for disease control becomes paramount for a sustainable and environmentally friendly crop production. Thus, fungicides should only be applied at critical stages for disease development, and only after the pathogen has been correctly identified. This chapter provides an overview of different weather-based disease models developed for assessing the real-time risk of epidemic development of the major fungal diseases (Septoria leaf blotch, leaf rusts and Fusarium head blight) of winter wheat in Luxembourg. [less ▲]

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See detailPhytomass estimation using eMODIS NDVI and ground data in arid rangelands of Morocco
Mahyou, Hamid ULiege; Tychon, Bernard ULiege; Lang, Marie ULiege et al

in African Journal of Range and Forage Science (2018)

The assessment of rangeland productivity in semi-extensively grazed arid rangelands is a prerequisite for livestock management in relation to sustainable use of pastoral resources. The objective of this ... [more ▼]

The assessment of rangeland productivity in semi-extensively grazed arid rangelands is a prerequisite for livestock management in relation to sustainable use of pastoral resources. The objective of this study was to assess rangeland productivity based on normalised difference vegetation index (NDVI) images. Data on phytomass were measured on 61 field samples in arid rangelands of Morocco, covering various rangeland categories during autumn (November) and spring (April), i.e. when phytomass is at low and high levels, respectively, for two consecutive years (2008 and 2009). Dekadal EROS Moderate Resolution Imaging Spectroradiometer (eMODIS) NDVI data were linearly regressed to field measurements for these four periods. Results show that phytomass values were correlated with NDVI during spring, with R 2 and RMSE values of 0.82 and 0.3 t ha−1, respectively. This study indicates there is a high potential for operational use of remotely sensed data to estimate rangeland phytomass of semi-extensively grazed rangelands. [less ▲]

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See detailEO_Regions_Science: Basic Research in support of EO_Regions!
Orban, Anne ULiege; Barbier, Christian ULiege; Billen, Roland ULiege et al

Conference (2018, January)

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See detailAquaCrop and ICT to improve irrigation efficiencies
Wellens, Joost ULiege; Wahbi, Amar; Tychon, Bernard ULiege et al

in FAO /IAEA Soils Newsletter (2018), 40(2),

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See detailHigh-resolution simulations of natural and agricultural ecosystems over Belgium with the CARAIB Dynamic Vegetation Model
Jacquemin, Ingrid ULiege; Dury, Marie ULiege; Henrot, Alexandra-Jane ULiege et al

Conference (2017, November 17)

CARAIB (for CARbon Assimilation In the Biosphere) is a state-of-the-art dynamic vegetation model (DVM), initially designed to study the role of the vegetation in the global carbon cycle and the vegetation ... [more ▼]

CARAIB (for CARbon Assimilation In the Biosphere) is a state-of-the-art dynamic vegetation model (DVM), initially designed to study the role of the vegetation in the global carbon cycle and the vegetation behavior as a function of climate and soil. Motivated by the requirements of ecosystem management and land use planning studies, CARAIB was recently improved so as to deal with both natural and agricultural ecosystems and at a high resolution of 1km over Belgium. A new module, for crops and meadows, was added in the model, which deals with the specific processes (phenology) and management (sowing, harvesting,…) of these ecosystems. The spatial and temporal validation was carried out with different data sources : agricultural statistics, eddy-covariance site, field measurements,… The addition of the crop module has led to the improvement of the surface scheme, from now on including dynamic land use and land cover information. As well as describes the evolution of physical and biological processes, CARAIB has become an interesting tool to assess the sustainability under climate change of the ecological systems, in particular by the approach of the ecosystem goods and services. Indeed, if some model outputs can be directly read as quantitative indicators of ecosystem services (e.g. carbon sequestration), we have translated some of them to get, e.g., the crop yield (from net primary productivity) or an estimation of the soil erosion for simulation at the parcel level (from runoff and parcels characteristics). But whether an ecosystem services or land use planning studies, the crucial point for CARAIB is the landscape dynamics, which is not considered by the model, in the absence of anthropogenic, economic and societal factors in the system. In order to overcome this lack, CARAIB is now coupled with an agent-based model (ABM), to compose a land surface dynamics (LSD) module. The productivity and growth of natural and managed vegetation is given by the DVM to the ABM, which determines the shifts in land use and land cover. The LSD module is able to represent the mutual interactions between ecological and socio-economic systems and thus, to assess the sustainability of the different climate and socio-economic scenarios tested. [less ▲]

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See detailCrowdsourcing for agricultural applications: A review of uses and opportunities for a farmsourcing approach
Minet, Julien ULiege; Curnel, Yannick; Gobin, Anne et al

in Computers and Electronics in Agriculture (2017), 142, Part A

Abstract Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper ... [more ▼]

Abstract Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper, we reviewed crowdsourcing initiatives in agricultural science and farming activities and further discussed the particular characteristics of this approach in the field of agriculture. On-going crowdsourcing initiatives in agriculture were analysed and categorised according to their crowdsourcing component. We identified eight types of agricultural data and information that can be generated from crowdsourcing initiatives. Subsequently we described existing methods of quality control of the crowdsourced data. We analysed the profiles of potential contributors in crowdsourcing initiatives in agriculture, suggested ways for increasing farmers’ participation, and discussed the on-going initiatives in the light of their target beneficiaries. While crowdsourcing is reported to be an efficient way of collecting observations relevant to environmental monitoring and contributing to science in general, we pointed out that crowdsourcing applications in agriculture may be hampered by privacy issues and other barriers to participation. Close connections with the farming sector, including extension services and farm advisory companies, could leverage the potential of crowdsourcing for both agricultural research and farming applications. This paper coins the term of farmsourcing as a professional crowdsourcing strategy in farming activities and provides a source of recommendations and inspirations for future collaborative actions in agricultural crowdsourcing. [less ▲]

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See detailAssessment of AquaCrop for winter wheat using satellite derived fCover data
Mohamed Sallah, Abdoul-Hamid ULiege; Wellens, Joost ULiege; Tychon, Bernard ULiege et al

in 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (2017, June 29)

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See detailPotato monitoring in Belgium with "watchITgrow"
Piccard, Isabelle; Gobin, Anne; Wellens, Joost ULiege et al

in 19th International Workshop on the Analysis of Multitemporal Remote Sensing Images (2017, June 29)

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See detailImproving fodder biomass modeling in the sahelian zone of Niger using the multiple linear regression method
Garba, Issa ULiege; Djaby, Bakary ULiege; Salifou, Illa et al

in International Journal for Research in Applied Science and Engineering Technology (2017), 5(5), 1627-1639

This study was carried out in Niger and aims to propose an improved fodder biomass estimate model using the Multiple Linear Regression (MRM) method. The work was carried out with measurements of ... [more ▼]

This study was carried out in Niger and aims to propose an improved fodder biomass estimate model using the Multiple Linear Regression (MRM) method. The work was carried out with measurements of herbaceous mass (in situ) made from 2001 to 2012 by the Ministry of Livestock and Animal Industry of Niger MEIA); rainfalls observed by the Niger Meteorological Office and the meteorological variables from the European Center for Medium - Range Weather Forecasts (ECMWF), processed in AgrometShell (AMS) to derive the agro- meteorological variables; the SPOT VEGETATION NDVI satellite images processed in the "Vegetation Analysis in Space and Time" (VAST) program to derive biophysical variables from the annual NDVI decadal series and finally the estimated rainfall known as RFE from the American institution "Famine Early Warning Systems Network "(FEWSNET) for the calculation of annual rainfall totals. The model was performed by multiple linear regressions with the ascending step – by - step procedure for the selection of variables based on the adjusted R² and the RMSE. Leave One Out Cross Validation (LOOICV) was used to calculate the validation R² and a systematic diagnosis of residues to better characterize the model. Throughout the (national) study area, MRM performed an adjusted R² of 0.68 and a RMSE of 282 kg. Ha-1, the difference between the RMSE of the calibration and that of the validation is 3.72 kg.ha-1. However, it is necessary to continue this research with other indices such as LAI and FAPAR and EVI. Also, it would be interesting to explore ways such as: taking into account the foliage of the trees, adjusting the metrics to the phenology of the herbaceous plants, and those of the woody ones. This work will improve the quality of information used to plan development actions in favor of Niger society in order to protect it against pastoral crises. [less ▲]

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See detailValidation of herbaceous biomass assessment model for sahelian rangelands (biomasah) in Niger.
Garba, Issa ULiege; Salifou, Illa; Djaby, Bakary ULiege et al

in International Journal of Current Research (2017), 9(4), 48992-48999

This study was carried out in the pastoral zone of Niger with the aim of validating outputs of the BIOMASAH model developed by the AGRHYMET Regional Centre (ARC) relative to real data collected over the ... [more ▼]

This study was carried out in the pastoral zone of Niger with the aim of validating outputs of the BIOMASAH model developed by the AGRHYMET Regional Centre (ARC) relative to real data collected over the 2001-2011 period by the Ministry Livestock and Animal Industries (MEIA) of Niger. We used parametric tests (t-tests) and nonparametric tests (Wilcoxon and sign tests) for mean comparisons. A correlation analysis was performed by calculating Pearson’s r, Spearman’s ρ, Kendall’s T and Hoeffding’s D correlation coefficients. The results showed that the BIOMASAH model generally overestimated biomass (983.17 vs. 591.17 kg/ha) with a highly significant difference relative to the field findings (P <.0001). Pearson’s r (0.15), Spearman’sρ (0.22) Kendall’s T (0.13) and Hoeffding’s D (0.1) correlation coefficients were low but highly significant (p <.0001). Grazing pressure and spatiotemporal variability of rainfall helped explain the noted differences. [less ▲]

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See detailMapping of zones at risk (ZAR) in West Africaby using NGI, VCI and SNDVI from the e-station.
Garba, Issa ULiege; Salifou, Illa; Sallah, Abdoul Hamid et al

in International Journal of Advanced Research (2017), 5(4), 1376-1386

This work is carried out at the AGRHYMET Regional Centre (ARC)-CILSS as part of the African Monitoring of Environment for Sustainable Development (AMESD) project. The analysis protocol has been improved ... [more ▼]

This work is carried out at the AGRHYMET Regional Centre (ARC)-CILSS as part of the African Monitoring of Environment for Sustainable Development (AMESD) project. The analysis protocol has been improved under the Monitoring of Environment for Security in Africa (MESA) project. The MESA Project has been designed on the achievements of AMESD; its overall objective is to provide African countries with access to Earth Observation data for environmental monitoring and sustainable development. The specific objective of this study is to develop an operational analysis protocol for vegetation monitoring in general and especially for crops and pastures. Three vegetation indices were used: Vegetation Condition Index (VCI), Normalized Growth Index (NGI) and Standardized Normalized Difference Vegetation Index (SNDVI). The analysis of these drought indices is based on taking into account the agro-climatic characteristics of the Sahelian region, the comparison of the NGI profile (per administrative unit) from year X (in progress) to the maximum NGI profiles, minimum and average of the time series data (1998 to year x-1) and evidence convergence. Six years of application of the method and validation actions carried out concluded that it is possible to determine the zones at risk (ZAR) in order to anticipate food crises. [less ▲]

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See detailPerformance of similarity analysis in the estimation of forage yields in the Sahelian zone of Niger
Garba, Issa ULiege; Salifou, Illa; Djaby, Bakary ULiege et al

in International Journal of Scientific and Engineering Research (2017), 8(2), 1072-1088

The study aims to test the performance of similarity analysis in herbaceous fodder biomass estimate in the Nigerian pastoral zone, in a context of insecurity and precipitation spatiotemporal variability ... [more ▼]

The study aims to test the performance of similarity analysis in herbaceous fodder biomass estimate in the Nigerian pastoral zone, in a context of insecurity and precipitation spatiotemporal variability. It is carried out on the time series of NDVI decadal images of SPOT VEGETATION for the period from 2001 to 2012 and on fodder biomasses measured in situ during the same period. Similarity analysis compares NDVI seasonal patterns to detect similar years using three criteria: the RMSE (Root Mean squared error), the MAD (Mean absolute Deviation), and R². Exploratory statistical analyzes with bootstrap are carried out to better characterize the observations resulting from the simulation. Moreover, the analysis of the parametric and non-parametric correlations is carried out to evaluate the level of link between the simulated data and the real data. The t test and the Wilcoxon test are then carried out in order to compare the means of the actual biomasses with those obtained by the similarity analysis. At the local level, the results indicate that the R² is more efficient than the RMSE and the MAD which have almost the same performances. The results of the similarity calculated with R² can be used as a proxy to the herbaceous phytomass measured in situ, as there is no significant difference between the simulated mean and the mean measured at the 1% threshold. On the other hand, the results of the similarity calculated with the RMSE and the MAD are not exploitable. Parametric and nonparametric correlations are all significant at the 1% threshold. However, the R² are low and vary between 0.32 and 0.45. It therefore seems necessary to continue the research, as numerous studies have revealed very good links between certain indices like the FAPAR, the EVI and the LAI and the aerial phytomasse. [less ▲]

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See detailOn the use of decision-support tools for improved irrigation management: AquaCrop-based applications
Wellens, Joost ULiege; Raes, Dirk; Tychon, Bernard ULiege

in Elshorbagy, Amin; Kulshreshtha, Suren (Eds.) Current perspectives on irrigation and drainage (2017)

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See detailCaractérisation morphologique des cuvettes oasiennes du Centre-Est du Niger
Barké, Mahamadou Karimou; Oussein, Issa; Bielders, Charles et al

in Physio-Géo: Géographie Physique et Environnement (2017), 11

Situées en zone semi-aride à aride du Niger, les cuvettes oasiennes du département de Gouré sont actuellement menacées d'ensablement en raison de la dégradation du couvert végétal et d'un accroissement de ... [more ▼]

Situées en zone semi-aride à aride du Niger, les cuvettes oasiennes du département de Gouré sont actuellement menacées d'ensablement en raison de la dégradation du couvert végétal et d'un accroissement de l'efficacité érosive des vents. Afin de comprendre les processus d'ensablement autour de ces cuvettes, une caractérisation de leurs formes et orientations a été entreprise. Le coefficient de compacité de GRAVELIUS a permis de mettre en évidence des cuvettes circulaires (8,5 %), ovales (46,8 %), amiboïdes (10,9 %), étirées (17,6 %) et très étirées à tendance amiboïde (16,1 %). Les cuvettes oasiennes de forme circulaire ou ovale renvoient à des drains partiellement comblés par les apports éoliens. Les formes étirées et très étirées sont liées à un morcèlement du réseau hydrographique par des édifices dunaires. Enfin, la mesure de l'orientation a permis d'apprécier la distribution entre quatre secteurs majeurs : E-O (22,8 %), N-S (21,4 %), NE-SO (21,6%) et SE-NO (34,3 %). Les cuvettes orientées E-O et NE-SO sont associées à des dunes longitudinales et celles orientées N-S et SE-NO à des dunes transversales. [less ▲]

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See detailPossibilités d'utilisation de Google EarthTM pour le suivi du couvert forestier de forêts claires en zone soudanienne au Bénin
Idjigberou, Eudes Shègoun; Tychon, Bernard ULiege

in Annales de l'Université de Parakou - série "Sciences naturelles et Agronomie" (2017), 7(1), 54-63

Dans un contexte général de dégradation continue des forêts, le développement des méthodes pour le suivi du couvert forestier devient nécessaire. Cette étude a exploré le potentiel d’utilisation de Google ... [more ▼]

Dans un contexte général de dégradation continue des forêts, le développement des méthodes pour le suivi du couvert forestier devient nécessaire. Cette étude a exploré le potentiel d’utilisation de Google EarthTM pour le suivi du couvert forestier des forêts claires réparties dans le domaine des savanes soudaniennes au nord du Bénin. Nous avons supposé que le recouvrement des peuplements ligneux de forêts claires estimé par placeau de 20 m x 20 m de dimensions, à partir des images de Google Earth est positivement corrélé avec la surface terrière calculée par placeau, sur la base des données d’inventaires forestiers. La méthode de classification supervisée « maximum Likelihood » a permis de classifier les extraits d’images numériques de Google Earth avec une précision globale supérieure à 94 %, en se basant sur trois classes d’occupation du sol (formation boisée et zones d’ombre, végétation herbacée, sol nu), et d’en extraire le recouvrement des ligneux par placeau. Les résultats montrent une forte corrélation entre la surface terrière calculée à partir des données de terrain et le taux de recouvrement des ligneux estimé à partir de Google Earth et suggère que Google EarthTM pourrait être utilisé pour le suivi du couvert forestier. Cependant, le manque de mise à jour régulière de la base de données de Google EarthTM et le décalage entre dates de capture d’images dans Google EarthTM et celles de collectes des données de terrain sont des contraintes à surmonter afin de rendre plus fiable l’utilisation de l’outil dans les pays en développement comme le Bénin. [less ▲]

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