Dominique Courault - Academia.edu (original) (raw)

Papers by Dominique Courault

Research paper thumbnail of Assessment and risk modeling of airborne enteric viruses emitted from wastewater reused for irrigation

Science of The Total Environment, 2017

Reclamation of wastewater (WW) for irrigation, after treatment represents a challenge that could ... more Reclamation of wastewater (WW) for irrigation, after treatment represents a challenge that could alleviate pressure on water resources and address the increasing demand for agriculture. However, the risks to human health must be assessed, particularly those related to human enteric viruses that resist standard treatments in most wastewater treatment plants (WWTP). The risks associated with exposure to viral bioaerosols near WWTP and near agricultural plots irrigated with WW are poorly documented. The objectives of this study were to 1) better characterize human enteric viruses found in bioaerosols near a "standard WWTP" and over fields irrigated with treated WW and 2) propose a numeric model to assess the health risk to populations located close to the irrigated areas, with particular attention to norovirus, which is responsible for most viral gastroenteritis in France. Water and air samples were collected at various locations in the largest French WW-irrigated site near Clermont-Ferrand, at the WWTP entrance and after treatment, in the air above activated sludge basins, and above fields irrigated with WW. Various enteric viruses were found in the water samples collected both before and after treatment. Norovirus was the most abundant with >10e4 genome copies/l (GC/L) before treatment and ~10e3 GC/L after treatment. Low quantities (<10e3GC/m3) were detected in the air above active sludge pools and irrigated plots. Hepatitis E virus was detected in all sampled compartments. A quantitative microbial risk assessment (QMRA) approach, including a simplified atmospheric dispersion model, allowed assessment of norovirus infection risk. The Bayesian QMRA approach considered wind speed measurements over 21years, and the variability and uncertainty of all measurements throughout the chain up to the risk. The probability of infection within one year for the most exposed WWTP employees was >10e-4 for strong wind speed (≥3m/s) and a constant emission rate of 8e3 GC/m3/s. This probability decreases by 3 log when the distance to the emission source is doubled. This information can aid development of safe water reuse policies in terms of local setback distance and wind conditions for wastewater reuse.

Research paper thumbnail of Analyse des hétérogénéites intraparcellaires des sols par télédétection

Research paper thumbnail of Irrigation Advisory Services: Farmers preferences and willingness to pay for innovation

Outlook on Agriculture

Irrigation Advisory Services (IAS) are powerful management instruments aiming to achieve the best... more Irrigation Advisory Services (IAS) are powerful management instruments aiming to achieve the best efficiency in irrigation water use. So far the literature on farmers’ preferences for a specific scheme design of IAS’ characteristics and the related willingness to pay (WTP) is scant. This study provides evidence on farmers’ preference towards six attributes related to the IAS configuration by using a hypothetical choice experiment. Data were collected from an original survey among 108 farmers from Spain, The Netherlands, Italy, Poland and South Africa. Moreover, we investigated the interplay between these preferences and the individual risk attitude (elicited through a lottery task) as a novel contribution. On average, the results suggest a clear farmers’ preference, especially for receiving weather forecasts from the service and for the feature related to water data recording; as the opposite, on average, crop water requirement seems irrelevant. Finally, we found that farmers’ WTP f...

Research paper thumbnail of STICS crop model and Sentinel-2 images for monitoring rice growth and yield in the Camargue region

Agronomy for Sustainable Development

Research paper thumbnail of Assessment of Agricultural Practices from Sentinel 1 2 Images Applied on Rice Fields to Get A Farm Typology in the Camargue Region

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium

Research paper thumbnail of Assessment of Agricultural Practices From Sentinel 1 and 2 Images Applied on Rice Fields to Develop a Farm Typology in the Camargue Region

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

In the global change context, an efficient management of the available resources has become one o... more In the global change context, an efficient management of the available resources has become one of the most important topics particularly for the sustainable crop development. Many questions concern the evolution of the rice farming systems in Camargue in Southeastern France, which play a crucial role in controlling the soil salinity. Their surface area significantly decreased from 20 000 ha in 2010 to 14 000 ha in 2014. The arrival of the new Sentinel satellites makes it possible to evaluate these crop evolutions. The objectives of this study were to propose operational methodologies to accurately assess the surface areas of the main crops, rice, wheat, and grassland, from classifications based on multispectral data; map agricultural practices (sowing and harvest residue burning); and elaborate a farm typology based on variables computed from remote sensing data to better understand the farming strategies. Dense time series of Sentinel images acquired at high spatial resolution (10 m) were analyzed for 2016 and 2017. A satisfactory accuracy was obtained for land use classification with 88% of correctly classified fields. The accuracy obtained for the estimation of the sowing date varied according to the studied year from 8 to 12 days, and burned areas were correctly identified (80%). The farm typology allowed to cluster farms at the territory level.

Research paper thumbnail of Assessment of Airborne Transport of Potential Contaminants in a Wind Tunnel

Journal of Irrigation and Drainage Engineering

The reuse of treated wastewater (TWW) for sprinkler irrigation could potentially diffuse pathogen... more The reuse of treated wastewater (TWW) for sprinkler irrigation could potentially diffuse pathogen-containing droplets off the application area. Wind and other unfavorable climatic factors enhance irrigation drift and bioaerosol dispersion, exposing humans to potentially severe health risks including the spread of diseases. Few studies have quantified bioaerosols during both spraying and airborne transport phases. Studies of effective sampling strategies to better qualify the dispersion process are also required. This paper presents experiments conducted in a wind tunnel for a deeper understanding of the effects of wind and temperature on pathogen or contaminant airborne dispersal and transport. It is the first time that passive collectors [polyvinyl chloride (PVC) lines] and active samplers (AGI-4 impinger) have been compared under analogous wind conditions using a fluorescent tracer. Droplet-size distribution was also investigated at 12 m from the boom with a NanoMoudi 122-NR cascade impactor in increasing wind conditions from 1 to 3 m s −1. PVC lines return a detailed evolution of the sprayed volume within a short range from the boom and for concentrated fluxes. Transport assessment of PVC lines indicates that transport and permanently airborne condition of the spray notably grow with increasing wind, resulting in a more compact and concentrated plume; mean transport increases from 0.13 to 1.18 L h −1 m −2 at 7.7 m from the nozzle as the wind velocity increases from 1 to 3 m s −1. AGI-4 appears more suitable to assess finely aerosolized conditions because of its greater sensitivity compared to PVC lines as shown for sample values less than 1 L h −1 m −2. The comparison between the AGI-4 and PVC lines shows higher values of recovery for the active samplers compared to the PVC lines. The total volume collected by the impingers was 2.93% of the sprayed volume, approximately twice that collected by PVC lines under analogous conditions, even though their sampling surface was only 1.54% that of PVC lines. Droplet-size distributions from the cascade impactor denote a median volume diameter from 1.1 to 2 μm, for the nozzle type used, and a relevant reduction in recovery at stronger wind velocities. An empirical relation time of flight is proposed as a first step in developing decision models that can be used to make sprinkler irrigation safe and to define standards for TWW reuse in agricultural practices (e.g., safe distance of application depending upon wind conditions and droplet-size distribution).

Research paper thumbnail of Mapping Paddy Rice Using Sentinel-1 SAR Time Series in Camargue, France

Remote Sensing

This study proposes an effective method to map rice crops using the Sentinel-1 SAR (Synthetic Ape... more This study proposes an effective method to map rice crops using the Sentinel-1 SAR (Synthetic Aperture Radar) time series over the Camargue region, Southern France. First, the temporal behavior of the SAR backscattering coefficient over 832 plots containing different crop types was analyzed. Through this analysis, the rice cultivation was identified using metrics derived from the Gaussian profile of the VV/VH time series (3 metrics), the variance of the VV/VH time series (one metric), and the slope of the linear regression of the VH time series (one metric). Using the derived metrics, rice plots were mapped through two different approaches: decision tree and Random Forest (RF). To validate the accuracy of each approach, the classified rice map was compared to the available national data. Similar high overall accuracy was obtained using both approaches. The overall accuracy obtained using a simple decision tree reached 96.3%, whereas an overall accuracy of 96.6% was obtained using th...

Research paper thumbnail of Estimation of Rice Height and Biomass Using Multitemporal SAR Sentinel-1 for Camargue, Southern France

Remote Sensing

The research and improvement of methods to be used for crop monitoring are currently major challe... more The research and improvement of methods to be used for crop monitoring are currently major challenges, especially for radar images due to their speckle noise nature. The European Space Agency’s (ESA) Sentinel-1 constellation provides synthetic aperture radar (SAR) images coverage with a 6-day revisit period at a high spatial resolution of pixel spacing of 20 m. Sentinel-1 data are considerably useful, as they provide valuable information of the vegetation cover. The objective of this work is to study the capabilities of multitemporal radar images for rice height and dry biomass retrievals using Sentinel-1 data. To do this, we train Sentinel-1 data against ground measurements with classical machine learning techniques (Multiple Linear Regression (MLR), Support Vector Regression (SVR) and Random Forest (RF)) to estimate rice height and dry biomass. The study is carried out on a multitemporal Sentinel-1 dataset acquired from May 2017 to September 2017 over the Camargue region, southern...

Research paper thumbnail of Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France

Remote Sensing

The development and improvement of methods to map agricultural land cover are currently major cha... more The development and improvement of methods to map agricultural land cover are currently major challenges, especially for radar images. This is due to the speckle noise nature of radar, leading to a less intensive use of radar rather than optical images. The European Space Agency Sentinel-1 constellation, which recently became operational, is a satellite system providing global coverage of Synthetic Aperture Radar (SAR) with a 6-days revisit period at a high spatial resolution of about 20 m. These data are valuable, as they provide spatial information on agricultural crops. The aim of this paper is to provide a better understanding of the capabilities of Sentinel-1 radar images for agricultural land cover mapping through the use of deep learning techniques. The analysis is carried out on multitemporal Sentinel-1 data over an area in Camargue, France. The data set was processed in order to produce an intensity radar data stack from May 2017 to September 2017. We improved this radar ti...

Research paper thumbnail of Observation de la végétation depuis l'espace

La Météorologie

L'arrivée de nouvelles données satellitaires en accès libre (notamment du programme européen Sent... more L'arrivée de nouvelles données satellitaires en accès libre (notamment du programme européen Sentinel de Copernicus) fait avancer la caractérisation de l'occupation des sols et des cycles de l'eau et du carbone. La résolution spatiale décamétrique de ces données, disponibles à une fréquence élevée, permet de produire des variables biogéophysiques à l'échelle des parcelles agricoles. Des applications en agrométéorologie sont possibles, mais également pour la validation et l'amélioration des modèles des surfaces terrestres utilisés en météorologie et en climat. Deux nouvelles missions de l'Agence spatiale européenne, Biomass et Flex, dont les lancements sont programmés respectivement pour 2021 et 2022, vont apporter des connaissances nouvelles sur la photosynthèse et le stockage de carbone par les forêts.

Research paper thumbnail of Contribution of Remote Sensing for Crop and Water Monitoring

Land Surface Remote Sensing in Agriculture and Forest, 2016

Research paper thumbnail of List of Authors

Land Surface Remote Sensing in Agriculture and Forest, 2016

Research paper thumbnail of Downscaling Meteosat Land Surface Temperature over a Heterogeneous Landscape Using a Data Assimilation Approach

Remote Sensing, 2016

A wide range of environmental applications require the monitoring of land surface temperature (LS... more A wide range of environmental applications require the monitoring of land surface temperature (LST) at frequent intervals and fine spatial resolutions, but these conditions are not offered nowadays by the available space sensors. To overcome these shortcomings, LST downscaling methods have been developed to derive higher resolution LST from the available satellite data. This research concerns the application of a data assimilation (DA) downscaling approach, the genetic particle smoother (GPS), to disaggregate Meteosat 8 LST time series (3 kmˆ5 km) at finer spatial resolutions. The methodology was applied over the Crau-Camargue region in Southeastern France for seven months in 2009. The evaluation of the downscaled LSTs has been performed at a moderate resolution using a set of coincident clear-sky MODIS LST images from Aqua and Terra platforms (1 kmˆ1 km) and at a higher resolution using Landsat 7 data (60 mˆ60 m). The performance of the downscaling has been assessed in terms of reduction of the biases and the root mean square errors (RMSE) compared to prior model-simulated LSTs. The results showed that GPS allows downscaling the Meteosat LST product from 3ˆ5 km 2 to 1ˆ1 km 2 scales with a RMSE less than 2.7 K. Finer scale downscaling at Landsat 7 resolution showed larger errors (RMSE around 5 K) explained by land cover errors and inter-calibration issues between sensors. Further methodology improvements are finally suggested.

Research paper thumbnail of The PRECOS framework: Measuring the impacts of the global changes on soils, water, agriculture on territories to better anticipate the future

Journal of environmental management, Jan 14, 2016

In a context of increased land and natural resources scarcity, the possibilities for local author... more In a context of increased land and natural resources scarcity, the possibilities for local authorities and stakeholders of anticipating evolutions or testing the impact of envisaged developments through scenario simulation are new challenges. PRECOS's approach integrates data pertaining to the fields of water and soil resources, agronomy, urbanization, land use and infrastructure etc. It is complemented by a socio-economic and regulatory analysis of the territory illustrating its constraints and stakes. A modular architecture articulates modeling software and spatial and temporal representations tools. It produces indicators in three core domains: soil degradation, water and soil resources and agricultural production. As a territory representative of numerous situations of the Mediterranean Basin (urban pressures, overconsumption of spaces, degradation of the milieus), a demonstration in the Crau's area (Southeast of France) has allowed to validate a prototype of the approac...

Research paper thumbnail of Estimation of surface fluxes in a small agricultural area using the three-dimensional atmospheric model Meso-NH and remote sensing data

Http Dx Doi Org 10 5589 M03 044, Jun 2, 2014

To provide an accurate water budget over a whole basin, hydrological models need to know the spat... more To provide an accurate water budget over a whole basin, hydrological models need to know the spatial variability of evapotranspiration at the watershed scale. The three-dimensional (3D) atmospheric models can provide such estimations at a regional scale, since they calculate the different energy and water fluxes by accounting for the landscape heterogeneity with a mesh grid varying from a few metres to several kilometres. We have used such a transfer model (Meso-NH) at a high spatial scale (50 m) to simulate the small agricultural region of the Alpilles (4 km × 5 km), where an experiment took place in 1997 and included intense ground measurements on different types of crops and airborne and satellite data collection. It was the first time that this model was used at such a fine resolution. The aim of this paper is to analyze the effects of the various crops on the spatial variability of the main energy fluxes, particularly evapotranspiration. We also wished to validate Meso-NH from this important available dataset. All input parameters were derived from remote sensing or airborne data: leaf area index (LAI) and albedo were computed from polarization and directionality of the earth's reflectances (POLDER) images. Roughness length was estimated combining both a land-use map obtained from Satellite pour l'Observation de la Terre (SPOT) images and the POLDER images. Maps of the main energy fluxes and temperatures were simulated for two periods in April and June and showed large spatial variations because of differences in soil moisture and in roughness of the crop types. Comparisons between the simulations and the measurements gave satisfactory results. Thermal images acquired by the infrared airborne camera were in good agreement with the surface temperatures estimated by the model. Significant differences were observed when we compared, on the same area, the value of averaged fluxes with the value of fluxes calculated with averaged surface parameters. This was due to the nonlinearity processes associated with averaging of environmental variables. The interest in using a mesoscale model applied at microscale is that coherent structures can be observed in the surface boundary layer, particularly on transects of the vertical wind speed. Such structures cannot be simulated at a larger scale or analyzed with simplified models. Remote sensing data acquired at a fine spatial resolution are a useful tool to provide accurate surface parameters to such a model. This allows quantification of the effect of each crop type on the spatial variation of temperature and evapotranspiration and thus improves our knowledge of the water budget of an agricultural landscape and the watershed functioning. 754 Résumé. L'estimation de la variation spatiale de l'évapotranspiration à l'échelle d'un bassin versant est primordiale si l'on veut obtenir des bilans précis sur les échanges d'eau et d'énergie avec des modèles hydrologiques. Les modèles 3D simulant les transferts atmosphériques peuvent fournir des informations sur cette variation spatiale à des échelles régionales, car ils calculent les différents flux de surface, en tenant compte de l'hétérogénéité du paysage, simulé suivant des grilles qui peuvent varier de quelques centaines de mètres à plusieurs kilomètres. Nous avons utilisé un tel modèle, Meso-NH, afin d'étudier quel est l'impact des cultures sur les variations spatiales des flux et du climat à l'échelle d'une petite région agricole : la zone du projet ALPILLES/ReSeda (4 km × 5 km au sud est d'Avignon). En 1997, une expérimentation importante a eu lieu sur ce site avec de nombreuses mesures caractérisant le sol, la végétation et l'atmosphère, accompagnées d'images de divers capteurs satellitaires et aéroportés. Les principaux paramètres de surface intervenant pour l'estimation des flux d'énergie ont été dérivés à partir de ces données de télédétection. L'indice foliaire (LAI), la fraction de trous et l'albedo ont été obtenus à partir d'images POLDER. Des cartes de rugosité ont été élaborées en combinant des information SPOT et POLDER. Des simulations courtes ont permis d'obtenir des cartes des principaux flux d'énergie et des températures de l'air et de la surface à deux périodes en avril et en juin. La comparaison des simulations aux mesures donne

Research paper thumbnail of Study of Uncertainties from Evapotranspiration Models Applied to Landsat Data Over a Mediterranean Agricultural Region

A large variety of methods have been developed to retrieve surface energy fluxes, in particular e... more A large variety of methods have been developed to retrieve surface energy fluxes, in particular evapotranspiration (ET) from remote sensing data. As a lot of satellites provide a large amount of images at various spatial and temporal resolutions, it is necessary to evaluate the methods frequently used for ET mapping, as well as the methodologies used to estimate the input variables (albedo, surface temperature, emissivity, net radiation, LAI, NDVI). The work presented here aims to assess the modelling of uncertainties in ET estimations from multispectral data. Particular emphasis is given to albedo estimation and 24 different models are being tested from a Landsat-7 dataset. It was acquired over the Crau-Camargue region, located in South Eastern France, between 2007 and 2010. In parallel to these images, continuous ground measurements of albedo, land surface temperature (LST) and surface fluxes are acquired for the same period for different surfaces, including irrigated and dry grassland, natural vegetation and various crops. The results show that each albedo model shows a quite large error (>11%) when compared with ground measurements. Performances are different according to the site upon study and the spectral band considered. The comparison between the different albedo models shows that those are lower over coefficients sets that include the middle infrared bands. Despite these errors, it appears that according to the reliability of albedo estimation (RMSE R =11%), it is possible to retrieve latent heat flux estimates with an uncertainty around 10 W•m-2 (ranging from-20 to 25 W•m-2).

Research paper thumbnail of Soil moisture retrieval over irrigated grassland using X-band SAR data

Remote Sensing of Environment, 2016

The aim of this study was to develop an inversion approach to estimate surface soil moisture from... more The aim of this study was to develop an inversion approach to estimate surface soil moisture from X-band SAR data over irrigated grassland areas. This approach simulates a coupling scenario between Synthetic Aperture Radar (SAR) and optical images through the Water Cloud Model (WCM). A time series of SAR (TerraSAR-X and COSMO-SkyMed) and 2 optical (SPOT 4/5 and LANDSAT 7/8) images were acquired over an irrigated grassland region in southeastern France. An inversion technique based on multi-layer perceptron neural networks (NNs) was used to invert the Water Cloud Model (WCM) for soil moisture estimation. Three inversion configurations based on SAR and optical images were defined: (1) HH polarization, (2) HV polarization, and (3) both HH and HV polarizations, all with one vegetation descriptor derived from optical data. The investigated vegetation descriptors were the Normalized Difference Vegetation Index "NDVI", Leaf Area Index "LAI", Fraction of Absorbed Photosynthetically Active Radiation "FAPAR", and the Fractional vegetation COVER "FCOVER". These vegetation descriptors were derived from optical images. For the three inversion configurations, the NNs were trained and validated using a noisy synthetic dataset generated by the WCM for a wide range of soil moisture and vegetation descriptor values. The trained NNs were then validated from a real dataset composed of X-band SAR backscattering coefficients and vegetation descriptor derived from optical images. The use of X-band SAR measurements in HH polarization (in addition to one vegetation descriptor derived from optical images) yields more precise results on soil moisture (M v) estimates. In the case of NDVI derived from optical images as the vegetation descriptor, the Root Mean Square Error on M v estimates was 3.6 Vol.% for NDVI values between 0.45 and 0.75, and 6.1 Vol.% for NDVI between 0.75 and 0.90. Similar results were obtained regardless of the other vegetation descriptor used.

Research paper thumbnail of Uncertainty assessment of surface net radiation derived from Landsat images

Remote Sensing of Environment, 2016

The NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the... more The NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.

Research paper thumbnail of The MODIS (collection V006) BRDF/albedo product MCD43D: Temporal course evaluated over agricultural landscape

Remote Sensing of Environment, 2015

The assessment of uncertainties in satellite-derived global surface albedo products is a critical... more The assessment of uncertainties in satellite-derived global surface albedo products is a critical aspect for studying the climate, ecosystem change, hydrology or the Earth's radiant energy budget. However, it is challenged by the spatial scaling errors between satellite and field measurements. This study aims at evaluating the forthcoming MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V006) Bidirectional Reflectance Distribution Function (BRDF)/albedo product MCD43D over a Mediterranean agricultural area. Here, we present the results from the accuracy assessment of the MODIS blue-sky albedo. The analysis is based on collocated 2 comparisons with higher spatial resolution estimates from Formosat-2 that were first evaluated against local in situ measurements. The inter-sensor comparison is achieved by taking into account the effective point spread function (PSF) for MODIS albedo, modeled as Gaussian functions in the North-South and East-West directions. The equivalent PSF is estimated by correlation analysis between MODIS albedo and Formosat-2 convolved albedo. Results show that it is 1.2 to 2.0 times larger in the East-West direction as compared to the North-South direction. We characterized the equivalent PSF by a full width at half maximum size of 1920 m in East-West, 1200 m in North-South. This provided a very good correlation between the products, showing absolute (relative) Root Mean Square Errors from 0.004 to 0.013 (2% to 7%), and almost no bias. By inspecting 1-km plots homogeneous in land cover type, we found poorer performances over rice and marshes (i.e., relative Root Mean Square Error of about 11% and 7%, and accuracy of 0.011 and-0.008, respectively), and higher accuracy over dry and irrigated pastures, as well as orchards (i.e., relative uncertainty <3.8% and accuracy <0.003). The study demonstrates that neglecting the MODIS PSF when comparing the Formosat-2 albedo against the MODIS one induces an additional uncertainty up to 0.02 (10%) in albedo. The consistency between fine and coarse spatial resolution albedo estimates indicates the ability of the daily MCD43D product to reproduce reasonably well the dynamics of albedo.

Research paper thumbnail of Assessment and risk modeling of airborne enteric viruses emitted from wastewater reused for irrigation

Science of The Total Environment, 2017

Reclamation of wastewater (WW) for irrigation, after treatment represents a challenge that could ... more Reclamation of wastewater (WW) for irrigation, after treatment represents a challenge that could alleviate pressure on water resources and address the increasing demand for agriculture. However, the risks to human health must be assessed, particularly those related to human enteric viruses that resist standard treatments in most wastewater treatment plants (WWTP). The risks associated with exposure to viral bioaerosols near WWTP and near agricultural plots irrigated with WW are poorly documented. The objectives of this study were to 1) better characterize human enteric viruses found in bioaerosols near a "standard WWTP" and over fields irrigated with treated WW and 2) propose a numeric model to assess the health risk to populations located close to the irrigated areas, with particular attention to norovirus, which is responsible for most viral gastroenteritis in France. Water and air samples were collected at various locations in the largest French WW-irrigated site near Clermont-Ferrand, at the WWTP entrance and after treatment, in the air above activated sludge basins, and above fields irrigated with WW. Various enteric viruses were found in the water samples collected both before and after treatment. Norovirus was the most abundant with >10e4 genome copies/l (GC/L) before treatment and ~10e3 GC/L after treatment. Low quantities (<10e3GC/m3) were detected in the air above active sludge pools and irrigated plots. Hepatitis E virus was detected in all sampled compartments. A quantitative microbial risk assessment (QMRA) approach, including a simplified atmospheric dispersion model, allowed assessment of norovirus infection risk. The Bayesian QMRA approach considered wind speed measurements over 21years, and the variability and uncertainty of all measurements throughout the chain up to the risk. The probability of infection within one year for the most exposed WWTP employees was >10e-4 for strong wind speed (≥3m/s) and a constant emission rate of 8e3 GC/m3/s. This probability decreases by 3 log when the distance to the emission source is doubled. This information can aid development of safe water reuse policies in terms of local setback distance and wind conditions for wastewater reuse.

Research paper thumbnail of Analyse des hétérogénéites intraparcellaires des sols par télédétection

Research paper thumbnail of Irrigation Advisory Services: Farmers preferences and willingness to pay for innovation

Outlook on Agriculture

Irrigation Advisory Services (IAS) are powerful management instruments aiming to achieve the best... more Irrigation Advisory Services (IAS) are powerful management instruments aiming to achieve the best efficiency in irrigation water use. So far the literature on farmers’ preferences for a specific scheme design of IAS’ characteristics and the related willingness to pay (WTP) is scant. This study provides evidence on farmers’ preference towards six attributes related to the IAS configuration by using a hypothetical choice experiment. Data were collected from an original survey among 108 farmers from Spain, The Netherlands, Italy, Poland and South Africa. Moreover, we investigated the interplay between these preferences and the individual risk attitude (elicited through a lottery task) as a novel contribution. On average, the results suggest a clear farmers’ preference, especially for receiving weather forecasts from the service and for the feature related to water data recording; as the opposite, on average, crop water requirement seems irrelevant. Finally, we found that farmers’ WTP f...

Research paper thumbnail of STICS crop model and Sentinel-2 images for monitoring rice growth and yield in the Camargue region

Agronomy for Sustainable Development

Research paper thumbnail of Assessment of Agricultural Practices from Sentinel 1 2 Images Applied on Rice Fields to Get A Farm Typology in the Camargue Region

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium

Research paper thumbnail of Assessment of Agricultural Practices From Sentinel 1 and 2 Images Applied on Rice Fields to Develop a Farm Typology in the Camargue Region

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

In the global change context, an efficient management of the available resources has become one o... more In the global change context, an efficient management of the available resources has become one of the most important topics particularly for the sustainable crop development. Many questions concern the evolution of the rice farming systems in Camargue in Southeastern France, which play a crucial role in controlling the soil salinity. Their surface area significantly decreased from 20 000 ha in 2010 to 14 000 ha in 2014. The arrival of the new Sentinel satellites makes it possible to evaluate these crop evolutions. The objectives of this study were to propose operational methodologies to accurately assess the surface areas of the main crops, rice, wheat, and grassland, from classifications based on multispectral data; map agricultural practices (sowing and harvest residue burning); and elaborate a farm typology based on variables computed from remote sensing data to better understand the farming strategies. Dense time series of Sentinel images acquired at high spatial resolution (10 m) were analyzed for 2016 and 2017. A satisfactory accuracy was obtained for land use classification with 88% of correctly classified fields. The accuracy obtained for the estimation of the sowing date varied according to the studied year from 8 to 12 days, and burned areas were correctly identified (80%). The farm typology allowed to cluster farms at the territory level.

Research paper thumbnail of Assessment of Airborne Transport of Potential Contaminants in a Wind Tunnel

Journal of Irrigation and Drainage Engineering

The reuse of treated wastewater (TWW) for sprinkler irrigation could potentially diffuse pathogen... more The reuse of treated wastewater (TWW) for sprinkler irrigation could potentially diffuse pathogen-containing droplets off the application area. Wind and other unfavorable climatic factors enhance irrigation drift and bioaerosol dispersion, exposing humans to potentially severe health risks including the spread of diseases. Few studies have quantified bioaerosols during both spraying and airborne transport phases. Studies of effective sampling strategies to better qualify the dispersion process are also required. This paper presents experiments conducted in a wind tunnel for a deeper understanding of the effects of wind and temperature on pathogen or contaminant airborne dispersal and transport. It is the first time that passive collectors [polyvinyl chloride (PVC) lines] and active samplers (AGI-4 impinger) have been compared under analogous wind conditions using a fluorescent tracer. Droplet-size distribution was also investigated at 12 m from the boom with a NanoMoudi 122-NR cascade impactor in increasing wind conditions from 1 to 3 m s −1. PVC lines return a detailed evolution of the sprayed volume within a short range from the boom and for concentrated fluxes. Transport assessment of PVC lines indicates that transport and permanently airborne condition of the spray notably grow with increasing wind, resulting in a more compact and concentrated plume; mean transport increases from 0.13 to 1.18 L h −1 m −2 at 7.7 m from the nozzle as the wind velocity increases from 1 to 3 m s −1. AGI-4 appears more suitable to assess finely aerosolized conditions because of its greater sensitivity compared to PVC lines as shown for sample values less than 1 L h −1 m −2. The comparison between the AGI-4 and PVC lines shows higher values of recovery for the active samplers compared to the PVC lines. The total volume collected by the impingers was 2.93% of the sprayed volume, approximately twice that collected by PVC lines under analogous conditions, even though their sampling surface was only 1.54% that of PVC lines. Droplet-size distributions from the cascade impactor denote a median volume diameter from 1.1 to 2 μm, for the nozzle type used, and a relevant reduction in recovery at stronger wind velocities. An empirical relation time of flight is proposed as a first step in developing decision models that can be used to make sprinkler irrigation safe and to define standards for TWW reuse in agricultural practices (e.g., safe distance of application depending upon wind conditions and droplet-size distribution).

Research paper thumbnail of Mapping Paddy Rice Using Sentinel-1 SAR Time Series in Camargue, France

Remote Sensing

This study proposes an effective method to map rice crops using the Sentinel-1 SAR (Synthetic Ape... more This study proposes an effective method to map rice crops using the Sentinel-1 SAR (Synthetic Aperture Radar) time series over the Camargue region, Southern France. First, the temporal behavior of the SAR backscattering coefficient over 832 plots containing different crop types was analyzed. Through this analysis, the rice cultivation was identified using metrics derived from the Gaussian profile of the VV/VH time series (3 metrics), the variance of the VV/VH time series (one metric), and the slope of the linear regression of the VH time series (one metric). Using the derived metrics, rice plots were mapped through two different approaches: decision tree and Random Forest (RF). To validate the accuracy of each approach, the classified rice map was compared to the available national data. Similar high overall accuracy was obtained using both approaches. The overall accuracy obtained using a simple decision tree reached 96.3%, whereas an overall accuracy of 96.6% was obtained using th...

Research paper thumbnail of Estimation of Rice Height and Biomass Using Multitemporal SAR Sentinel-1 for Camargue, Southern France

Remote Sensing

The research and improvement of methods to be used for crop monitoring are currently major challe... more The research and improvement of methods to be used for crop monitoring are currently major challenges, especially for radar images due to their speckle noise nature. The European Space Agency’s (ESA) Sentinel-1 constellation provides synthetic aperture radar (SAR) images coverage with a 6-day revisit period at a high spatial resolution of pixel spacing of 20 m. Sentinel-1 data are considerably useful, as they provide valuable information of the vegetation cover. The objective of this work is to study the capabilities of multitemporal radar images for rice height and dry biomass retrievals using Sentinel-1 data. To do this, we train Sentinel-1 data against ground measurements with classical machine learning techniques (Multiple Linear Regression (MLR), Support Vector Regression (SVR) and Random Forest (RF)) to estimate rice height and dry biomass. The study is carried out on a multitemporal Sentinel-1 dataset acquired from May 2017 to September 2017 over the Camargue region, southern...

Research paper thumbnail of Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France

Remote Sensing

The development and improvement of methods to map agricultural land cover are currently major cha... more The development and improvement of methods to map agricultural land cover are currently major challenges, especially for radar images. This is due to the speckle noise nature of radar, leading to a less intensive use of radar rather than optical images. The European Space Agency Sentinel-1 constellation, which recently became operational, is a satellite system providing global coverage of Synthetic Aperture Radar (SAR) with a 6-days revisit period at a high spatial resolution of about 20 m. These data are valuable, as they provide spatial information on agricultural crops. The aim of this paper is to provide a better understanding of the capabilities of Sentinel-1 radar images for agricultural land cover mapping through the use of deep learning techniques. The analysis is carried out on multitemporal Sentinel-1 data over an area in Camargue, France. The data set was processed in order to produce an intensity radar data stack from May 2017 to September 2017. We improved this radar ti...

Research paper thumbnail of Observation de la végétation depuis l'espace

La Météorologie

L'arrivée de nouvelles données satellitaires en accès libre (notamment du programme européen Sent... more L'arrivée de nouvelles données satellitaires en accès libre (notamment du programme européen Sentinel de Copernicus) fait avancer la caractérisation de l'occupation des sols et des cycles de l'eau et du carbone. La résolution spatiale décamétrique de ces données, disponibles à une fréquence élevée, permet de produire des variables biogéophysiques à l'échelle des parcelles agricoles. Des applications en agrométéorologie sont possibles, mais également pour la validation et l'amélioration des modèles des surfaces terrestres utilisés en météorologie et en climat. Deux nouvelles missions de l'Agence spatiale européenne, Biomass et Flex, dont les lancements sont programmés respectivement pour 2021 et 2022, vont apporter des connaissances nouvelles sur la photosynthèse et le stockage de carbone par les forêts.

Research paper thumbnail of Contribution of Remote Sensing for Crop and Water Monitoring

Land Surface Remote Sensing in Agriculture and Forest, 2016

Research paper thumbnail of List of Authors

Land Surface Remote Sensing in Agriculture and Forest, 2016

Research paper thumbnail of Downscaling Meteosat Land Surface Temperature over a Heterogeneous Landscape Using a Data Assimilation Approach

Remote Sensing, 2016

A wide range of environmental applications require the monitoring of land surface temperature (LS... more A wide range of environmental applications require the monitoring of land surface temperature (LST) at frequent intervals and fine spatial resolutions, but these conditions are not offered nowadays by the available space sensors. To overcome these shortcomings, LST downscaling methods have been developed to derive higher resolution LST from the available satellite data. This research concerns the application of a data assimilation (DA) downscaling approach, the genetic particle smoother (GPS), to disaggregate Meteosat 8 LST time series (3 kmˆ5 km) at finer spatial resolutions. The methodology was applied over the Crau-Camargue region in Southeastern France for seven months in 2009. The evaluation of the downscaled LSTs has been performed at a moderate resolution using a set of coincident clear-sky MODIS LST images from Aqua and Terra platforms (1 kmˆ1 km) and at a higher resolution using Landsat 7 data (60 mˆ60 m). The performance of the downscaling has been assessed in terms of reduction of the biases and the root mean square errors (RMSE) compared to prior model-simulated LSTs. The results showed that GPS allows downscaling the Meteosat LST product from 3ˆ5 km 2 to 1ˆ1 km 2 scales with a RMSE less than 2.7 K. Finer scale downscaling at Landsat 7 resolution showed larger errors (RMSE around 5 K) explained by land cover errors and inter-calibration issues between sensors. Further methodology improvements are finally suggested.

Research paper thumbnail of The PRECOS framework: Measuring the impacts of the global changes on soils, water, agriculture on territories to better anticipate the future

Journal of environmental management, Jan 14, 2016

In a context of increased land and natural resources scarcity, the possibilities for local author... more In a context of increased land and natural resources scarcity, the possibilities for local authorities and stakeholders of anticipating evolutions or testing the impact of envisaged developments through scenario simulation are new challenges. PRECOS's approach integrates data pertaining to the fields of water and soil resources, agronomy, urbanization, land use and infrastructure etc. It is complemented by a socio-economic and regulatory analysis of the territory illustrating its constraints and stakes. A modular architecture articulates modeling software and spatial and temporal representations tools. It produces indicators in three core domains: soil degradation, water and soil resources and agricultural production. As a territory representative of numerous situations of the Mediterranean Basin (urban pressures, overconsumption of spaces, degradation of the milieus), a demonstration in the Crau's area (Southeast of France) has allowed to validate a prototype of the approac...

Research paper thumbnail of Estimation of surface fluxes in a small agricultural area using the three-dimensional atmospheric model Meso-NH and remote sensing data

Http Dx Doi Org 10 5589 M03 044, Jun 2, 2014

To provide an accurate water budget over a whole basin, hydrological models need to know the spat... more To provide an accurate water budget over a whole basin, hydrological models need to know the spatial variability of evapotranspiration at the watershed scale. The three-dimensional (3D) atmospheric models can provide such estimations at a regional scale, since they calculate the different energy and water fluxes by accounting for the landscape heterogeneity with a mesh grid varying from a few metres to several kilometres. We have used such a transfer model (Meso-NH) at a high spatial scale (50 m) to simulate the small agricultural region of the Alpilles (4 km × 5 km), where an experiment took place in 1997 and included intense ground measurements on different types of crops and airborne and satellite data collection. It was the first time that this model was used at such a fine resolution. The aim of this paper is to analyze the effects of the various crops on the spatial variability of the main energy fluxes, particularly evapotranspiration. We also wished to validate Meso-NH from this important available dataset. All input parameters were derived from remote sensing or airborne data: leaf area index (LAI) and albedo were computed from polarization and directionality of the earth's reflectances (POLDER) images. Roughness length was estimated combining both a land-use map obtained from Satellite pour l'Observation de la Terre (SPOT) images and the POLDER images. Maps of the main energy fluxes and temperatures were simulated for two periods in April and June and showed large spatial variations because of differences in soil moisture and in roughness of the crop types. Comparisons between the simulations and the measurements gave satisfactory results. Thermal images acquired by the infrared airborne camera were in good agreement with the surface temperatures estimated by the model. Significant differences were observed when we compared, on the same area, the value of averaged fluxes with the value of fluxes calculated with averaged surface parameters. This was due to the nonlinearity processes associated with averaging of environmental variables. The interest in using a mesoscale model applied at microscale is that coherent structures can be observed in the surface boundary layer, particularly on transects of the vertical wind speed. Such structures cannot be simulated at a larger scale or analyzed with simplified models. Remote sensing data acquired at a fine spatial resolution are a useful tool to provide accurate surface parameters to such a model. This allows quantification of the effect of each crop type on the spatial variation of temperature and evapotranspiration and thus improves our knowledge of the water budget of an agricultural landscape and the watershed functioning. 754 Résumé. L'estimation de la variation spatiale de l'évapotranspiration à l'échelle d'un bassin versant est primordiale si l'on veut obtenir des bilans précis sur les échanges d'eau et d'énergie avec des modèles hydrologiques. Les modèles 3D simulant les transferts atmosphériques peuvent fournir des informations sur cette variation spatiale à des échelles régionales, car ils calculent les différents flux de surface, en tenant compte de l'hétérogénéité du paysage, simulé suivant des grilles qui peuvent varier de quelques centaines de mètres à plusieurs kilomètres. Nous avons utilisé un tel modèle, Meso-NH, afin d'étudier quel est l'impact des cultures sur les variations spatiales des flux et du climat à l'échelle d'une petite région agricole : la zone du projet ALPILLES/ReSeda (4 km × 5 km au sud est d'Avignon). En 1997, une expérimentation importante a eu lieu sur ce site avec de nombreuses mesures caractérisant le sol, la végétation et l'atmosphère, accompagnées d'images de divers capteurs satellitaires et aéroportés. Les principaux paramètres de surface intervenant pour l'estimation des flux d'énergie ont été dérivés à partir de ces données de télédétection. L'indice foliaire (LAI), la fraction de trous et l'albedo ont été obtenus à partir d'images POLDER. Des cartes de rugosité ont été élaborées en combinant des information SPOT et POLDER. Des simulations courtes ont permis d'obtenir des cartes des principaux flux d'énergie et des températures de l'air et de la surface à deux périodes en avril et en juin. La comparaison des simulations aux mesures donne

Research paper thumbnail of Study of Uncertainties from Evapotranspiration Models Applied to Landsat Data Over a Mediterranean Agricultural Region

A large variety of methods have been developed to retrieve surface energy fluxes, in particular e... more A large variety of methods have been developed to retrieve surface energy fluxes, in particular evapotranspiration (ET) from remote sensing data. As a lot of satellites provide a large amount of images at various spatial and temporal resolutions, it is necessary to evaluate the methods frequently used for ET mapping, as well as the methodologies used to estimate the input variables (albedo, surface temperature, emissivity, net radiation, LAI, NDVI). The work presented here aims to assess the modelling of uncertainties in ET estimations from multispectral data. Particular emphasis is given to albedo estimation and 24 different models are being tested from a Landsat-7 dataset. It was acquired over the Crau-Camargue region, located in South Eastern France, between 2007 and 2010. In parallel to these images, continuous ground measurements of albedo, land surface temperature (LST) and surface fluxes are acquired for the same period for different surfaces, including irrigated and dry grassland, natural vegetation and various crops. The results show that each albedo model shows a quite large error (>11%) when compared with ground measurements. Performances are different according to the site upon study and the spectral band considered. The comparison between the different albedo models shows that those are lower over coefficients sets that include the middle infrared bands. Despite these errors, it appears that according to the reliability of albedo estimation (RMSE R =11%), it is possible to retrieve latent heat flux estimates with an uncertainty around 10 W•m-2 (ranging from-20 to 25 W•m-2).

Research paper thumbnail of Soil moisture retrieval over irrigated grassland using X-band SAR data

Remote Sensing of Environment, 2016

The aim of this study was to develop an inversion approach to estimate surface soil moisture from... more The aim of this study was to develop an inversion approach to estimate surface soil moisture from X-band SAR data over irrigated grassland areas. This approach simulates a coupling scenario between Synthetic Aperture Radar (SAR) and optical images through the Water Cloud Model (WCM). A time series of SAR (TerraSAR-X and COSMO-SkyMed) and 2 optical (SPOT 4/5 and LANDSAT 7/8) images were acquired over an irrigated grassland region in southeastern France. An inversion technique based on multi-layer perceptron neural networks (NNs) was used to invert the Water Cloud Model (WCM) for soil moisture estimation. Three inversion configurations based on SAR and optical images were defined: (1) HH polarization, (2) HV polarization, and (3) both HH and HV polarizations, all with one vegetation descriptor derived from optical data. The investigated vegetation descriptors were the Normalized Difference Vegetation Index "NDVI", Leaf Area Index "LAI", Fraction of Absorbed Photosynthetically Active Radiation "FAPAR", and the Fractional vegetation COVER "FCOVER". These vegetation descriptors were derived from optical images. For the three inversion configurations, the NNs were trained and validated using a noisy synthetic dataset generated by the WCM for a wide range of soil moisture and vegetation descriptor values. The trained NNs were then validated from a real dataset composed of X-band SAR backscattering coefficients and vegetation descriptor derived from optical images. The use of X-band SAR measurements in HH polarization (in addition to one vegetation descriptor derived from optical images) yields more precise results on soil moisture (M v) estimates. In the case of NDVI derived from optical images as the vegetation descriptor, the Root Mean Square Error on M v estimates was 3.6 Vol.% for NDVI values between 0.45 and 0.75, and 6.1 Vol.% for NDVI between 0.75 and 0.90. Similar results were obtained regardless of the other vegetation descriptor used.

Research paper thumbnail of Uncertainty assessment of surface net radiation derived from Landsat images

Remote Sensing of Environment, 2016

The NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the... more The NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner.

Research paper thumbnail of The MODIS (collection V006) BRDF/albedo product MCD43D: Temporal course evaluated over agricultural landscape

Remote Sensing of Environment, 2015

The assessment of uncertainties in satellite-derived global surface albedo products is a critical... more The assessment of uncertainties in satellite-derived global surface albedo products is a critical aspect for studying the climate, ecosystem change, hydrology or the Earth's radiant energy budget. However, it is challenged by the spatial scaling errors between satellite and field measurements. This study aims at evaluating the forthcoming MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V006) Bidirectional Reflectance Distribution Function (BRDF)/albedo product MCD43D over a Mediterranean agricultural area. Here, we present the results from the accuracy assessment of the MODIS blue-sky albedo. The analysis is based on collocated 2 comparisons with higher spatial resolution estimates from Formosat-2 that were first evaluated against local in situ measurements. The inter-sensor comparison is achieved by taking into account the effective point spread function (PSF) for MODIS albedo, modeled as Gaussian functions in the North-South and East-West directions. The equivalent PSF is estimated by correlation analysis between MODIS albedo and Formosat-2 convolved albedo. Results show that it is 1.2 to 2.0 times larger in the East-West direction as compared to the North-South direction. We characterized the equivalent PSF by a full width at half maximum size of 1920 m in East-West, 1200 m in North-South. This provided a very good correlation between the products, showing absolute (relative) Root Mean Square Errors from 0.004 to 0.013 (2% to 7%), and almost no bias. By inspecting 1-km plots homogeneous in land cover type, we found poorer performances over rice and marshes (i.e., relative Root Mean Square Error of about 11% and 7%, and accuracy of 0.011 and-0.008, respectively), and higher accuracy over dry and irrigated pastures, as well as orchards (i.e., relative uncertainty <3.8% and accuracy <0.003). The study demonstrates that neglecting the MODIS PSF when comparing the Formosat-2 albedo against the MODIS one induces an additional uncertainty up to 0.02 (10%) in albedo. The consistency between fine and coarse spatial resolution albedo estimates indicates the ability of the daily MCD43D product to reproduce reasonably well the dynamics of albedo.