Building a Data Set over 12 Globally Distributed Sites to Support the Development of Agriculture Monitoring Applications with Sentinel-2

Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel­2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel­2 for Agriculture” system.Instituto de Clima y AguaFil: Bontemps, Sophie. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Arias, Marcela. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Cara, Cosmin. CS Romania S.A.; RumaniaFil: Dedieu, Gérard. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Guzzonato, Eric. CS Systèmes d’Information; FranciaFil: Hagolle, Olivier. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Inglada, Jordi. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Matton, Nicolas. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Morin, David. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Popescu, Ramona. CS Romania S.A.; RumaniaFil: Rabaute, Thierry. CS Systèmes d’Information; FranciaFil: Savinaud, Mickael. CS Systèmes d’Information; FranciaFil: Sepulcre, Guadalupe. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Valero, Silvia. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Ahmad, Ijaz. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Bégué, Agnès. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Wu, Bingfang. Chinese Academy of Sciences. Institute of Remote Sensing and Digital Earth; República de ChinaFil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Diarra, Alhousseine. Université Cadi Ayyad. Faculté des Sciences Semlalia; MarruecosFil: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: French, Andrew. United States Department of Agriculture. Agricultural Research Service. Arid Land Agricultural Research Center; ArgentinaFil: Akhtar, Ibrar ul Hassan. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Kussul, Nataliia. National Academy of Sciences of Ukraine. Space Research Institute and State Space Agency of Ukraine; UcraniaFil: Lebourgeois, Valentine. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Le Page, Michel. Université Cadi Ayyad. Faculté des Sciences Semlalia. Laboratoire Mixte International TREMA; Marruecos. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Newby, Terrence. Agricultural Research Council; SudáfricaFil: Savin, Igor. V.V. Dokuchaev Soil Science Institute; RusiaFil: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Koetz, Benjamin. European Space Agency. European Space Research Institute; ItaliaFil: Defourny, Pierre. Université Catholique de Louvain. Earth and Life Institute; Bélgic

Suivi de l'évapotranspiration des cultures irriguées du Sud de la Méditerranée par télédétection multi-capteurs et modélisation globale

With the increasing pressure on water resources accentuated by the climate change threat, irrigated agriculture, especially in semi-arid zone, faced more challenges. Optimal management of water resources is essential in irrigated areas in order to avoid both excessive irrigation and water stress that is harmful to the growth of crops. In this context, proposing a simple, parsimonious and robust, easyto- use tool for monitoring the crop water requirement at different spatial and temporal scales would provide a tangible indicator of irrigation efficiency over irrigated perimeters. This thesis aims to evaluate and adapt several tools for monitoring the evapotranspiration of irrigated crops from the plot scale to the regional scale through the use of multi-sensor and multi-resolution remote sensing observations. Our study area is the Tensift watershed in Morocco, studied by LMI TREMA (Jarlan et al., 2015) and supported by the Tensift observatory. We identified 3 tools: a surface energy balance model (TSEB; Norman et al., 1995) driven by a radiometric temperature observation that provides indirect information on surface water status; the FAO-56 dual crop coefficient approach predicts the hydric status by computing the water balance but requires the know precisely the water input, very difficult to obtain on the plot scale of irrigated perimeters ; global modeling which, as opposed to the first two, is an autonomous approach requiring no external forcing. Firstly, the comparison of the TSEB model simulations with a set of experimental measurements collected on a plot scale during 2 consecutive agricultural seasons and with the results of the calibrated FAO-56 dual crop coefficient approach has shown that : - the TSEB model is very robust and offers acceptable performance for the prediction of evapotranspiration (RMSE <1mm / day during the two agricultural seasons); - a good capabilities of TSEB model for detection water stress; - a good ability also to partition the evapotranspiration between evaporation of the soil and transpiration of the plant. In the second step, we evaluated the predictive capacities of a global model that we developed on the basis of a time series of evapotranspiration observed in the field. Global modeling is based on the theory of the nonlinear dynamic systems theory. If it does not have the explanatory capabilities of the mechanistic models mentioned above, it may be a good alternative for predicting evapotranspiration. The analysis of the horizon of predictability of the global model that we obtained shows a limited interest for the farmers or the managers since this horizon does not exceed 3h. Nevertheless, this approach, very original in this context, remains particularly attractive and opens perspectives. Finally, we have developed a prototype, based on the TSEB model and using only MODIS free products and ERAInterim reanalyses, for monitoring evapotranspiration at Tensift watershed scale and over long periods. After an evaluation of the ERA-Interim products, we evaluated the prototype performance by (1) comparing the predictions of the energy balance components to the experimental data from Tensift observatory and (2) comparing the predicted monthly consumption at the main irrigated perimeters of the region with monthly water supplies provided by the regional office which manages these perimeters. Thus, there is a strong overestimation (almost a factor of 2) of the water consumed compared to the inflow of water, which could be related to the high number of boreholes in the region. This work and the tools developed opens perspectives for piloting and managing agricultural water in semi-arid regions.Avec la pression croissante sur les ressources en eau accentuée par la menace des changementsglobaux, l'agriculture irriguée, surtout dans les régions semi-arides, se trouve confrontée à denouvelles exigences. Une gestion optimale des ressources en eau est indispensable dans les périmètresirrigués afin d'éviter à la fois l'irrigation excessive et le stress hydrique dommageable aux cultures.Dans ce contexte, proposer un outil simple, parcimonieux et robuste, facile à mettre en placepermettant de suivre le besoin réel en eau des cultures, à différentes échelles spatio-temporelles,permettrait d’apporter un indicateur tangible quant à l’efficience de l’irrigation dans les périmètresirrigués. Ce travail de thèse a pour objectif d’évaluer et d’adapter plusieurs outils de suivi del’évapotranspiration des cultures irriguées de l’échelle parcellaire à l’échelle régionale par l’utilisationde la télédétection multi-capteurs et multi-résolution. Notre zone d’étude est le bassin versant duTensift au Maroc, objet d’étude du LMI TREMA (Jarlan et al., 2015) et support de l’observatoireTensift. Nous avons identifié 3 outils : un modèle de bilan d’énergie de surface (TSEB ; Norman et al.,1995) piloté par une observation de température radiométrique qui renseigne indirectement sur l’étathydrique de surface ; l’approche à coefficient cultural double de la FAO-56 (Allen et al., 1998) quiprédit l’état hydrique de surface par la résolution d’un bilan hydrique mais nécessite en contre-partiede connaître précisément les apports d’eau, grandeur très incertaine sur les périmètres irrigués àl’échelle parcellaire ; la modélisation globale qui, par opposition aux deux autres, est une approcheautonome ne nécessitant aucun forçage externe. Dans un premier temps, la confrontation dessimulations du modèle TSEB à un ensemble de mesures expérimentales recueillies à l’échelleparcellaire durant 2 saisons agricoles ainsi qu’à l’approche FAO-56 préalablement calibrée sur lesprincipales cultures de notre région d’étude sur la base de travaux antérieurs a permis de montrer que :- le modèle TSEB est très robuste et offre des performances acceptables pour la prédiction del’évapotranspiration (RMSE < 1mm/jour sur 4 sites lors de deux saisons agricoles) ; - les bonnescapacités de cet outil pour la détection de stress hydrique ; - une bonne aptitude également àpartitionner l’évapotranspiration entre évaporation du sol et transpiration de la plante. Dans un 2èmetemps, nous avons évalué les capacités prédictives d’un modèle global que nous avons développé surla base d’une série temporelle d’évapotranspiration observée sur le terrain. La modélisation globale estbasée sur la théorie des systèmes dynamique non-linéaire. Si elle ne possède pas les capacitésexplicatives des modèles mécanistes évoqués ci-dessus, peut être une bonne alternative pour laprévision de l’évapotranspiration. L’analyse de l’horizon de prévisibilité du modèle global que nousavons obtenu montre un intérêt limité pour les agriculteurs ou les gestionnaires puisque cet horizonn’excède pas 3h. Néanmoins, cette approche, très originale dans ce contexte, reste particulièrementséduisante et ouvre plusieurs perspectives. Enfin, nous avons développé un prototype « tout satellite »,basé sur le modèle TSEB et qui utilise uniquement les produits gratuits MODIS et les ré-analysesERA-Interim, pour le suivi spatialisée et à long terme de la consommation en eau des cultures dans lebassin versant du Tensift. Après une évaluation des forçages ERA-Interim, nous avons évalué laperformance du prototype par (1) confrontation des prédictions des composantes du bilan d’énergieaux données expérimentales de l’observation Tensift et (2) confrontation de la consommationmensuelle prédite au niveau des principaux périmètres irrigués de la région aux apports d’eaumensuels fournis par l’office régional qui gère ces périmètres..

Monitoring of evapotranspiration over irrigated crops in the South Mediterranean region using multi-sensor remote sensing observations and global modeling

Avec la pression croissante sur les ressources en eau accentuée par la menace des changementsglobaux, l'agriculture irriguée, surtout dans les régions semi-arides, se trouve confrontée à denouvelles exigences. Une gestion optimale des ressources en eau est indispensable dans les périmètresirrigués afin d'éviter à la fois l'irrigation excessive et le stress hydrique dommageable aux cultures.Dans ce contexte, proposer un outil simple, parcimonieux et robuste, facile à mettre en placepermettant de suivre le besoin réel en eau des cultures, à différentes échelles spatio-temporelles,permettrait d’apporter un indicateur tangible quant à l’efficience de l’irrigation dans les périmètresirrigués. Ce travail de thèse a pour objectif d’évaluer et d’adapter plusieurs outils de suivi del’évapotranspiration des cultures irriguées de l’échelle parcellaire à l’échelle régionale par l’utilisationde la télédétection multi-capteurs et multi-résolution. Notre zone d’étude est le bassin versant duTensift au Maroc, objet d’étude du LMI TREMA (Jarlan et al., 2015) et support de l’observatoireTensift. Nous avons identifié 3 outils : un modèle de bilan d’énergie de surface (TSEB ; Norman et al.,1995) piloté par une observation de température radiométrique qui renseigne indirectement sur l’étathydrique de surface ; l’approche à coefficient cultural double de la FAO-56 (Allen et al., 1998) quiprédit l’état hydrique de surface par la résolution d’un bilan hydrique mais nécessite en contre-partiede connaître précisément les apports d’eau, grandeur très incertaine sur les périmètres irrigués àl’échelle parcellaire ; la modélisation globale qui, par opposition aux deux autres, est une approcheautonome ne nécessitant aucun forçage externe. Dans un premier temps, la confrontation dessimulations du modèle TSEB à un ensemble de mesures expérimentales recueillies à l’échelleparcellaire durant 2 saisons agricoles ainsi qu’à l’approche FAO-56 préalablement calibrée sur lesprincipales cultures de notre région d’étude sur la base de travaux antérieurs a permis de montrer que :- le modèle TSEB est très robuste et offre des performances acceptables pour la prédiction del’évapotranspiration (RMSE < 1mm/jour sur 4 sites lors de deux saisons agricoles) ; - les bonnescapacités de cet outil pour la détection de stress hydrique ; - une bonne aptitude également àpartitionner l’évapotranspiration entre évaporation du sol et transpiration de la plante. Dans un 2èmetemps, nous avons évalué les capacités prédictives d’un modèle global que nous avons développé surla base d’une série temporelle d’évapotranspiration observée sur le terrain. La modélisation globale estbasée sur la théorie des systèmes dynamique non-linéaire. Si elle ne possède pas les capacitésexplicatives des modèles mécanistes évoqués ci-dessus, peut être une bonne alternative pour laprévision de l’évapotranspiration. L’analyse de l’horizon de prévisibilité du modèle global que nousavons obtenu montre un intérêt limité pour les agriculteurs ou les gestionnaires puisque cet horizonn’excède pas 3h. Néanmoins, cette approche, très originale dans ce contexte, reste particulièrementséduisante et ouvre plusieurs perspectives. Enfin, nous avons développé un prototype « tout satellite »,basé sur le modèle TSEB et qui utilise uniquement les produits gratuits MODIS et les ré-analysesERA-Interim, pour le suivi spatialisée et à long terme de la consommation en eau des cultures dans lebassin versant du Tensift. Après une évaluation des forçages ERA-Interim, nous avons évalué laperformance du prototype par (1) confrontation des prédictions des composantes du bilan d’énergieaux données expérimentales de l’observation Tensift et (2) confrontation de la consommationmensuelle prédite au niveau des principaux périmètres irrigués de la région aux apports d’eaumensuels fournis par l’office régional qui gère ces périmètres...With the increasing pressure on water resources accentuated by the climate change threat, irrigated agriculture, especially in semi-arid zone, faced more challenges. Optimal management of water resources is essential in irrigated areas in order to avoid both excessive irrigation and water stress that is harmful to the growth of crops. In this context, proposing a simple, parsimonious and robust, easyto- use tool for monitoring the crop water requirement at different spatial and temporal scales would provide a tangible indicator of irrigation efficiency over irrigated perimeters. This thesis aims to evaluate and adapt several tools for monitoring the evapotranspiration of irrigated crops from the plot scale to the regional scale through the use of multi-sensor and multi-resolution remote sensing observations. Our study area is the Tensift watershed in Morocco, studied by LMI TREMA (Jarlan et al., 2015) and supported by the Tensift observatory. We identified 3 tools: a surface energy balance model (TSEB; Norman et al., 1995) driven by a radiometric temperature observation that provides indirect information on surface water status; the FAO-56 dual crop coefficient approach predicts the hydric status by computing the water balance but requires the know precisely the water input, very difficult to obtain on the plot scale of irrigated perimeters ; global modeling which, as opposed to the first two, is an autonomous approach requiring no external forcing. Firstly, the comparison of the TSEB model simulations with a set of experimental measurements collected on a plot scale during 2 consecutive agricultural seasons and with the results of the calibrated FAO-56 dual crop coefficient approach has shown that : - the TSEB model is very robust and offers acceptable performance for the prediction of evapotranspiration (RMSE <1mm / day during the two agricultural seasons); - a good capabilities of TSEB model for detection water stress; - a good ability also to partition the evapotranspiration between evaporation of the soil and transpiration of the plant. In the second step, we evaluated the predictive capacities of a global model that we developed on the basis of a time series of evapotranspiration observed in the field. Global modeling is based on the theory of the nonlinear dynamic systems theory. If it does not have the explanatory capabilities of the mechanistic models mentioned above, it may be a good alternative for predicting evapotranspiration. The analysis of the horizon of predictability of the global model that we obtained shows a limited interest for the farmers or the managers since this horizon does not exceed 3h. Nevertheless, this approach, very original in this context, remains particularly attractive and opens perspectives. Finally, we have developed a prototype, based on the TSEB model and using only MODIS free products and ERAInterim reanalyses, for monitoring evapotranspiration at Tensift watershed scale and over long periods. After an evaluation of the ERA-Interim products, we evaluated the prototype performance by (1) comparing the predictions of the energy balance components to the experimental data from Tensift observatory and (2) comparing the predicted monthly consumption at the main irrigated perimeters of the region with monthly water supplies provided by the regional office which manages these perimeters. Thus, there is a strong overestimation (almost a factor of 2) of the water consumed compared to the inflow of water, which could be related to the high number of boreholes in the region. This work and the tools developed opens perspectives for piloting and managing agricultural water in semi-arid regions

Profile of the in silico secretome of the palm dieback pathogen, Fusarium oxysporum f. sp. albedinis, a fungus that puts natural oases at risk.

Understanding biotic changes that occur alongside climate change constitute a research priority of global significance. Here, we address a plant pathogen that poses a serious threat to life on natural oases, where climate change is already taking a toll and severely impacting human subsistence. Fusarium oxysporum f. sp. albedinis is a pathogen that causes dieback disease on date palms, a tree that provides several critical ecosystem services in natural oases; and consequently, of major importance in this vulnerable habitat. Here, we assess the current state of global pathogen spread, we annotate the genome of a sequenced pathogen strain isolated from the native range and we analyse its in silico secretome. The palm dieback pathogen secretes a large arsenal of effector candidates including a variety of toxins, a distinguished profile of secreted in xylem proteins (SIX) as well as an expanded protein family with an N-terminal conserved motif [SG]PC[KR]P that could be involved in interactions with host membranes. Using agrobiodiversity as a strategy to decrease pathogen infectivity, while providing short term resilient solutions, seems to be widely overcome by the pathogen. Hence, the urgent need for future mechanistic research on the palm dieback disease and a better understanding of pathogen genetic diversity

Modified Penman–Monteith equation for monitoring evapotranspiration of wheat crop: Relationship between the surface resistance and remotely sensed stress index

International audienceEvapotranspiration (ET) plays an essential role for detecting plant water status, estimating crop water needs and optimising irrigation management. Accurate estimates of ET at field scale are therefore critical. The present paper investigates a remote sensing and modelling coupled approach for monitoring actual ET of irrigated wheat crops in the semi-arid region of Tensift Al Haouz (Morocco). The ET modelling is based on a modified Penman-Monteith equation obtained by introducing a simple empirical relationship between surface resistance (r(c)) and a stress index (SI). SI is estimated from Landsat-derived land surface temperature (LST) combined with the LST endmembers (in wet and dry conditions) simulated by a surface energy balance model driven by meteorological forcing and Landsat-derived fractional vegetation cover. The proposed model is first calibrated using eddy covariance measurements of ET during one growing season (2015-2016) over an experimental flood irrigated wheat field located within the irrigated perimeter named R3. It is then validated during the same growing season over another drip-irrigated wheat field located in the same perimeter. Next, the proposed ET model is implemented over a 10 x 10 km(2) area in R3 using a time series of Landsat-7/8 reflectance and LST data. The comparison between modelled and measured ET fluxes indicates that the model works well. The Root Mean Square Error (RMSE) values over drip and flood sites were 13 and 12 W m(-2), respectively. The proposed approach has a great potential for detecting crop water stress and estimating crop water requirements over large areas along the agricultural seaso

Medium-Resolution Mapping of Evapotranspiration at the Catchment Scale Based on Thermal Infrared MODIS Data and ERA-Interim Reanalysis over North Africa

International audienceAccurate quantification of evapotranspiration (ET) at the watershed scale remains an important research challenge for managing water resources in arid and semiarid areas. In this study, daily latent heat flux (LE) maps at the kilometer scale were derived from the two-source energy budget (TSEB) model fed by the MODIS leaf area index (LAI), land surface temperature (LST) products, and meteorological data from ERA-Interim reanalysis from 2001 to 2015 on the Tensift catchment (center of Morocco). As a preliminary step, both ERA-Interim and predicted LE at the time of the satellite overpass are evaluated in comparison to a large database of in situ meteorological measurements and eddy covariance (EC) observations, respectively. ERA-Interim compared reasonably well to in situ measurements, but a positive bias on air temperature was highlighted because meteorological stations used for the evaluation were mainly installed on irrigated fields while the grid point of ERA-Interim is representative of larger areas including bare (and hot) soil. Likewise, the predicted LE was in good agreement with the EC measurements gathered on the main crops of the region during 15 agricultural seasons with a correlation coefficient r = 0.70 and a reasonable bias of 30 W/m2. After extrapolating the instantaneous LE estimates to ET daily values, monthly ET was then assessed in comparison to monthly irrigation water amounts provided by the local agricultural office added to CRU precipitation dataset with a reasonable agreement; the relative error was more than 89% but the correlation coefficient r reached 0.80. Seasonal and interannual evapotranspiration was analyzed in relation to local climate and land use. Lastly, the potential use for improving the early prediction of grain yield, as well as detecting newly irrigated areas for arboriculture, is also discussed. The proposed method provides a relatively simple way for obtaining spatially distributed daily estimates of ET at the watershed scale, especially for not ungauged catchments