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1. Remote sensing of the Earth's soil color in space and time

Author

Rizzo, Rodnei, Wadoux, Alexandre M.J.-C., Demattê, José A.M., Minasny, Budiman, Barrón, Vidal, Ben-Dor, Eyal, Francos, Nicolas, Savin, Igor, Poppiel, Raul, Silvero, Nelida E.Q., Terra, Fabrício da Silva, Rosin, Nícolas Augusto, Rosas, Jorge Tadeu Fim, Greschuk, Lucas Tadeu, Ballester, Maria V.R., Gómez, Andrés Mauricio Rico, Belllinaso, Henrique, Safanelli, José Lucas, Chabrillat, Sabine, Fiorio, Peterson R., Das, Bhabani Sankar, Malone, Brendan P., Zalidis, George, Tziolas, Nikolaos, Tsakiridis, Nikolaos, Karyotis, Konstantinos, Samarinas, Nikiforos, Kalopesa, Eleni, Gholizadeh, Asa, Shepherd, Keith D., Milewski, Robert, Vaudour, Emmanuelle, Wang, Changkun, and Salama, Elsayed Said Mohamed

Published
2023
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7. Retrieving Soil Moisture from Sentinel-1: Limitations over Certain Crops and Sensitivity to the First Soil Thin Layer.

Author

Bazzi, Hassan, Baghdadi, Nicolas, Nino, Pasquale, Napoli, Rosario, Najem, Sami, Zribi, Mehrez, and Vaudour, Emmanuelle

Subjects
SOIL moisture, COVER crops, SOIL moisture measurement, NORMALIZED difference vegetation index, CROPS, GROUND vegetation cover
Abstract

This paper presents a comparison between the Sentinel-1 (S1)/Sentinel-2 (S2)-derived soil moisture products at plot scale (S2MP) and in situ soil moisture measurements at a 10 cm depth for several winter and summer crops. Specifically, the paper discusses the consistency between the in situ soil moisture measurements, usually performed at a 10 cm soil depth, and the variable S1 C-band penetration depth in soil due to soil humidity conditions, vegetation development and S1 acquisition configuration. The aim is to provide end users with the strength and limitations of S1-derived soil moisture, mainly the S2MP soil moisture product, for their further applications. Both the estimated and measured soil moisture (SM) were evaluated over three testing fields in a Mediterranean climatic context, with crop cycles including wheat, tomato, cover crops and soybeans. The main results showed that the comparison between the S2MP-estimated SM based on S1 backscattering (at ~5 cm depth) with a 10 cm in situ SM is not always relevant during the crop cycle. In dry conditions, the S1 SM significantly underestimated the 10 cm SM measurements with an underestimation that could reach around 20 vol.% in some extremely dry conditions. This high underestimation was mainly due to the difference between the topsoil SM captured by the S1 sensor and the 10 cm in depth SM. Moderately wet conditions due to rainfall or irrigation showed less of a difference between the S1-estimated SM and the 10 cm in situ SM and varying between −10 and −5 vol.% due to the homogeneity of the SM at different soil depths. For extremely wet conditions, the S1 SM started to underestimate the SM values with an underestimation that can reach an order of −10 vol.%. A comparison of the S1-estimated SM as a function of the vegetation development showed that, for the studied crop types, the S1 SM estimates are only valid for low and moderate vegetation cover with a Normalized Difference Vegetation Index (NDVI) of less than 0.7. For dense vegetation cover (NDVI > 0.7), overestimations of the SM (average bias of about 4 vol.%) are mainly observed for developed tomato and soybean crops due to fruits' emergence, whereas an extreme underestimation (average bias reaching −15.5 vol.%) is found for developed wheat cover due to the vertical structure of the wheat kernels. The results also suggest that the optimal SM estimations by S1 could be mainly obtained at low radar incidence angles (incidence angle less than 35°). [ABSTRACT FROM AUTHOR]

Published
2024
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10. Remote Sensing Data for Digital Soil Mapping in French Research—A Review

Author

Richer-de-Forges, Anne C., primary, Chen, Qianqian, additional, Baghdadi, Nicolas, additional, Chen, Songchao, additional, Gomez, Cécile, additional, Jacquemoud, Stéphane, additional, Martelet, Guillaume, additional, Mulder, Vera L., additional, Urbina-Salazar, Diego, additional, Vaudour, Emmanuelle, additional, Weiss, Marie, additional, Wigneron, Jean-Pierre, additional, and Arrouays, Dominique, additional

Published
2023
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13. BIODIVERSITY – A new space mission to monitor Earth ecosystems at fine scale

Author

BRIOTTET, Xavier, primary, BAJJOUK, Touria, additional, CHAMI, Malik, additional, DELACOURT, Christophe, additional, FERET, Jean-Baptiste, additional, JACQUEMOUD, Stephane, additional, MINGHELLI, Audrey, additional, SHEEREN, David, additional, WEBER, Christiane, additional, FABRE, Sophie, additional, ADELINE, Karine, additional, VAUDOUR, Emmanuelle, additional, LUQUE, Sandra, additional, DEVILLE, Yannick, additional, SOUDANI, Kamel, additional, and VERPOOTER, Charles, additional

Published
2022
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14. BIODIVERSITY – Une Nouvelle Mission Spatiale Pour Le Suivi Des Ecosystèmes A Une Echelle Fine

Author

Briottet, Xavier, Bajjouk, Touria, Chami, Malik, Delacourt, Christophe, Feret, Jean-baptiste, Jacquemoud, Stephane, Minghelli, Audrey, Sheeren, David, Weber, Christiane, Fabre, Sophie, Adeline, Karine, Vaudour, Emmanuelle, Luque, Sandra, Deville, Yannick, Soudani, Kamel, and Verpooter, Charles

Subjects
critical zone, zone critique, milieu urbain, imaging spectroscopy, space mission, biodiversité, coastal ecosystems, écosystèmes côtiers, hyperspectral, vegetation, mission spatiale, soil quality, imagerie hyperspectrale, végétation, qualité des sols, biodiversity, urban area
Abstract

Imaging spectroscopy has demonstrated its interest in characterizing the biochemical, biophysical and structural properties of vegetation, natural and agricultural soils, as well as artificial surfaces. Following the Hyperion mission, new space missions have emerged (PRISMA, EnMap), or are under study (CHIME, SBG). However, one of their main limitations lies in their spatial resolution that induces a large number of mixed pixels reducing their potential for discrimination for very heterogeneous areas. The BIODIVERSITY mission aims to complement these space missions with better GSD acquisitions (typically 8-10 m) with a 5-day revisit on targeted reference sites with identified and well-located characteristics. It will thus make it possible, in particular, to answer two scientific issues that will design the instrument. The first issue concerns the spatial and temporal distribution of vegetation traits in species assemblages; these traits are associated with the resilience of terrestrial ecosystems, anthropogenic influences, and the biodiversity of ecosystems in terms of species composition and assemblages. The second issue relates to improving our knowledge of coastal areas and inland waters in terms of biodiversity, water quality and bathymetry, in order to assess the impact of human activity on their ecosytems. The scientific challenges as well as the user requirements for such a mission are presented for each application., L’imagerie hyperspectrale a démontré son intérêt pour la caractérisation des propriétés biochimiques, biophysiques et structurelles de la végétation, des sols naturels et agricoles ainsi que des surfaces artificialisées. A la suite de la mission Hyperion, de nouvelles missions spatiales ont vu le jour (PRISMA, EnMAP), ou sont en phase d’étude (SBG, CHIME). Ces spectro-imageurs ont une résolution spatiale au sol de l’ordre de 30 m, un large champ de vue et peuvent couvrir de vastes zones du globe terrestre afin de caractériser les écosystèmes terrestres et océaniques avec un temps de revisite variant de 4 à 16 jours. Néanmoins, leur résolution spatiale est limitée ce qui induit un nombre important de pixels mixtes réduisant leur potentiel de discrimination pour des zones hétérogènes. La mission BIODIVERSITY a pour objectif de compléter ces missions par des acquisitions de meilleure résolution spatiale (typiquement 8-10 m) avec une revisite de l’ordre de 5 jours sur des sites de référence ciblés possédant des caractéristiques identifiées et bien localisées. Elle permettra ainsi de répondre à deux problématiques scientifiques qui vont dimensionner l’instrument. La première problématique porte sur la distribution spatiale et temporelle des traits de la végétation dans les assemblages d’espèces ; ces traits sont associés à la résilience des écosystèmes terrestres, aux influences anthropiques et à la biodiversité des écosystèmes en termes de composition et d’assemblages en espèces. La seconde problématique porte sur l’amélioration de nos connaissances des zones côtières et des eaux continentales en termes de biodiversité, de qualité des eaux et de bathymétrie, pour ensuite évaluer l’impact de l’activité anthropique sur leurs écosystèmes. Enfin, ces deux applications qui déterminent les spécifications de l’instrument seront complétées par l’étude, à fine résolution spatiale, de l’impact des pratiques de gestion des sols dans un processus environnemental tels que le stockage du carbone dans les sols, l’infiltration et la rétention d’eau en surface ou l’érosion des sols. Elles ouvrent également de nouvelles voies pour évaluer comment les matériaux urbains influencent notre environnement proche et pour caractériser les pollutions urbaine et industrielle. Les défis scientifiques ainsi que les exigences-utilisateurs pour une telle mission sont présentés pour chaque application.

Published
2022

15. Crop-specific phenology from Sentinel-1 & 2 and disaggregated PROBA-V data

Author

Rivas, Henry, Delbart, Nicolas, Ottle, Catherine, Maignan, Fabienne, Vaudour, Emmanuelle, Le Toan, Thuy, Laboratoire Interdisciplinaire des Energies de Demain (LIED (UMR_8236)), Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[SDE.ES]Environmental Sciences/Environmental and Society
Abstract

International audience

Published
2022

16. Crop-specific phenology from disaggregated Medium Spatial Resolution optical data

Author

Rivas, Henry, Delbart, Nicolas, Ottle, Catherine, Maignan, Fabienne, Vaudour, Emmanuelle, Le Toan, Thuy, Laboratoire Interdisciplinaire des Energies de Demain (LIED (UMR_8236)), Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[SDE.ES]Environmental Sciences/Environmental and Society
Abstract

International audience

Published
2022

17. Satellite Imagery to Map Topsoil Organic Carbon Content over Cultivated Areas: An Overview

Author

Vaudour, Emmanuelle, primary, Gholizadeh, Asa, additional, Castaldi, Fabio, additional, Saberioon, Mohammadmehdi, additional, Borůvka, Luboš, additional, Urbina-Salazar, Diego, additional, Fouad, Youssef, additional, Arrouays, Dominique, additional, Richer-de-Forges, Anne C., additional, Biney, James, additional, Wetterlind, Johanna, additional, and Van Wesemael, Bas, additional

Published
2022
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18. Digital soil mapping from territories to globe. Progress and challenges. Invited talk

Author

Arrouays, D., Richer-De-Forges, Anne C, Libohova, Zamir, Minasny, B., Mulder, Vera Leatitia., Poggio, Laura, Roudier, Pierre, Bourennane, Hocine, Lagacherie, Philippe, Martelet, Guillaume, Martin, Manuel P, Nehlig, Pierre, Saby, Nicolas P. A., Vaudour, Emmanuelle, Salazar, Diego Fernando Urbina, Gomez, Cécile, Barthès, Bernard, Lemercier, Blandine, Meersmans, Jeroen, Walter, Christian, Chen, Songchao, and Richer-de-Forges, Anne

Subjects
[SDU.STU] Sciences of the Universe [physics]/Earth Sciences, [SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study
Published
2022

19. The Theia 'Digital Soil Mapping' Scientific Expertise Centre of France

Author

Richer-De-Forges, Anne C, Lagacherie, Philippe, Arrouays, Dominique, Bialkowski, Anne, Bourennane, Hocine, Briottet, Xavier, Fouad, Youssef, Gomez, Cécile, Jacquemoud, Stéphane, Lemercier, Blandine, Maisongrande, Philippe, Martelet, Guillaume, Martin, Manuel P, Michot, Didier, Pichelin, Pascal, Saby, Nicolas P. A., Tissoux, Hélène, Vaudour, Emmanuelle, Wadoux, Alexandre M.J.-C., Walter, Christian, Puissant, Anne, Richer-de-Forges, Anne, InfoSol (InfoSol), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Unité de Science du Sol (Orléans) (URSols), ONERA / DOTA, Université de Toulouse [Toulouse], ONERA-PRES Université de Toulouse, Sol Agro et hydrosystème Spatialisation (SAS), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Indo-French Cell for Water Sciences (IFCWS), Indian Institute of Science [Bangalore] (IISc Bangalore), Institut de Physique du Globe de Paris (IPGP (UMR_7154)), Institut national des sciences de l'Univers (INSU - CNRS)-Université de La Réunion (UR)-Institut de Physique du Globe de Paris (IPG Paris)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Centre National d'Études Spatiales [Toulouse] (CNES), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire Image, Ville, Environnement (LIVE), and Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.STU] Sciences of the Universe [physics]/Earth Sciences, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences
Abstract

International audience; pas de résumé

Published
2022

20. Scientific Committee

Author

Fouad, Youssef, primary, Carrere, Véronique, additional, Chabrillat, Sabine, additional, Demarez, Valérie, additional, Roujean, Jean Louis, additional, Lacaze, Roselyne, additional, Pattey, Elizabeth, additional, Kayitakire, Francois, additional, Ceschia, Eric, additional, Brunet, Yves, additional, Sheeren, David, additional, Vaudour, Emmanuelle, additional, Alleaume, Samuel, additional, Bappel, Eric, additional, Corgne, Samuel, additional, Arvor, Damien, additional, Catry, Thibault, additional, Rudant, Jean-Paul, additional, Gaetano, Raffaele, additional, Mougin, Eric, additional, Weiss, Marie, additional, Michez, Adrien, additional, Bauwens, Sébastien, additional, Bonnet, Stéphanie, additional, Lejeune, Philippe, additional, Belouard, Thierry, additional, Barbier, Nicolas, additional, Rejou, Maxime, additional, Vincent, Grégoire, additional, Baghdadi, Nicolas, additional, and Zribi, Mehrez, additional

Published
2016
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21. Using Sentinel-2 Images for Soil Organic Carbon Content Mapping in Croplands of Southwestern France. The Usefulness of Sentinel-1/2 Derived Moisture Maps and Mismatches between Sentinel Images and Sampling Dates

Author

Urbina-Salazar, Diego, Vaudour, Emmanuelle, Baghdadi, Nicolas, Ceschia, Eric, Richer-de-Forges, Anne, Lehmann, Sébastien, Arrouays, Dominique, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), InfoSol (InfoSol), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
soil organic carbon, southwestern france, topographic wetness index, Science, sentinel-2, digital soil mapping, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, soil moisture, croplands, slaking crust sensitivity index
Abstract

International audience; In agronomy, soil organic carbon (SOC) content is important for the development and growth of crops. From an environmental monitoring viewpoint, SOC sequestration is essential for mitigating the emission of greenhouse gases into the atmosphere. SOC dynamics in cropland soils should be further studied through various approaches including remote sensing. In order to predict SOC content over croplands in southwestern France (area of 22,177 km²), this study addresses (i) the influence of the dates on which Sentinel-2 (S2) images were acquired in the springs of 2017–2018 as well as the influence of the soil sampling period of a set of samples collected between 2005 and 2018, (ii) the use of soil moisture products (SMPs) derived from Sentinel-1/2 satellites to analyze the influence of surface soil moisture on model performance when included as a covariate, and (iii) whether the spatial distribution of SOC as mapped using S2 is related to terrain-derived attributes. The influences of S2 image dates and soil sampling periods were analyzed for bare topsoil. The dates of the S2 images with the best performance (RPD ≥ 1.7) were 6 April and 26 May 2017, using soil samples collected between 2016 and 2018. The soil sampling dates were also analyzed using SMP values. Soil moisture values were extracted for each sample and integrated into partial least squares regression (PLSR) models. The use of soil moisture as a covariate had no effect on the prediction performance of the models; however, SMP values were used to select the driest dates, effectively mapping topsoil organic carbon. S2 was able to predict high SOC contents in the specific soil types located on the old terraces (mesas) shaped by rivers flowing from the southwestern Pyrénées.

Published
2021

23. Potential of Sentinel-2 Satellite Images for Monitoring Green Waste Compost and Manure Amendments in Temperate Cropland

Author

Dodin, Maxence, Smith, Hunter D., Levavasseur, Florent, Hadjar, Dalila, Houot, Sabine, Vaudour, Emmanuelle, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and University of Florida [Gainesville] (UF)

Subjects
agroecology, soil organic carbon, [SPI]Engineering Sciences [physics], reflectance, amendments, Science, tillage, [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, Sentinel-2, exogenous organic matter, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study
Abstract

International audience; Increasing attention has been placed on the agroecological impact of applying exogenous organic matter (EOM) amendments, such as green waste compost (GWC) and livestock manure, to agricultural landscapes. However, monitoring the frequency and locality of this practice poses a major challenge, as these events are typically unreported. The purpose of this study is to evaluate the utility of Sentinel-2 imagery for the detection of EOM amendments. Specifically, we investigated the spectral shift resulting from GWC and manure application at two spatial scales, satellite and proximal. At the satellite scale, multispectral Sentinel-2 image pairs were analyzed before and after EOM application to six cultivated fields in the Versailles Plain, France. At the proximal scale, multi-temporal spectral field measurements were taken of experimental plots consisting of 14 total treatments: EOM variety, amendment quantity (15, 30 and 60 t.ha−1) and tillage. The Sentinel-2 images showed significant spectral differences before and after EOM application. Exogenous Organic Matter Indices (EOMI) were developed and analyzed for separative performance. The best performing index was EOMI2, using the B4 and B12 Sentinel-2 spectral bands. At the proximal scale, simulated Sentinel-2 reflectance spectra, which were created using field measurements, successfully monitored all EOM treatments for three days, except for the buried green waste compost at a rate of 15 t.ha−1.

Published
2021

26. StoreSoilC : Evaluer le potentiel de stockage du carbone organique dans les sols au moyen d’une approche statistique « data-driven » Etude de cas d’une petite région agricole

Author

CREME, Alexandra, Vaudour, Emmanuelle, Arrouays, Dominique, Richer-de-Forges, Anne C, Levavasseur, Florent, Chenu, Claire, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, InfoSol (InfoSol), and Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2019

29. Soil Science Challenges in a New Era: A Transdisciplinary Overview of Relevant Topics

Author

Rodrigo-Comino, Jesús, primary, López-Vicente, Manuel, additional, Kumar, Vinod, additional, Rodríguez-Seijo, Andrés, additional, Valkó, Orsolya, additional, Rojas, Claudia, additional, Pourghasemi, Hamid Reza, additional, Salvati, Luca, additional, Bakr, Noura, additional, Vaudour, Emmanuelle, additional, Brevik, Eric C, additional, Radziemska, Maja, additional, Pulido, Manuel, additional, Di Prima, Simone, additional, Dondini, Marta, additional, de Vries, Wim, additional, Santos, Erika S, additional, Mendonça-Santos, Maria de Lourdes, additional, Yu, Yang, additional, and Panagos, Panos, additional

Published
2020
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30. Mosaicking approaches for predicting topsoil organic carbon content from sentinel-2 time series

Author

Vaudour, Emmanuelle, Gomez, Cécile, Loiseau, Thomas, Lagacherie, Philippe, Arrouays, Dominique, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), InfoSol (InfoSol), and Institut National de la Recherche Agronomique (INRA)

Subjects
remote sensing, monitoring, carbon, [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, mapping, ComputingMilieux_MISCELLANEOUS, soil
Abstract

National audience

Published
2019

31. Monitoring grassland management effects on soil organic carbon – a matter of scale

Author

Creme, Alexandra, Rumpel, Cornelia, Saby, Nicolas, Vaudour, Emmanuelle, Malone, Sparkle, Decau, M.L., Chabbi, Abad, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris Saclay (COmUE), Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris), Institut National de la Recherche Agronomique (INRA)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), InfoSol (InfoSol), Institut National de la Recherche Agronomique (INRA), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), and ProdInra, Migration

Subjects
[SDV] Life Sciences [q-bio], [SDE] Environmental Sciences, [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2019

32. Impact of acquisition date on the prediction performance of topsoil organic carbon from single date or multidate Sentinel-2 images

Author

Vaudour, Emmanuelle, Gomez, Cécile, Ali, Leila, Loiseau, Thomas, Lagacherie, Philippe, Arrouays, Dominique, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris Saclay (COmUE), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), InfoSol (InfoSol), and Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, GeneralLiterature_MISCELLANEOUS
Abstract

International audience; The implementation of information technology solutions in agriculture is required, particularly in the area of sensing and mapping systems to provide critical data for decision support and help different stakeholders (agricultural producers and researchers) to evaluate the status of soil and propose soil management strategies in the context of climate change. New sensor technologies allow collecting fine-scale information to provide spatial and temporal variability related data on soil, crop and environmental factors. Over the last few decades, visible and near infrared (visNIR) spectroscopy provided a high through put tool to carry out large sample quantities. This enables the efficient assessment of soil property patterns such as C, N, clay content. Furthermore, technology development and information management systems (e.g., geographic information systems, photogrammetry and remote sensing techniques, global positioning systems, sensors and communication devices for real-time soil sensing and monitoring) have been advanced to deal with agricultural soil sustainability and productivity. The purpose of the session is to present the current knowledge on relevant methodologies and techniques concerning soil diagnostics and crop monitoring by using remote sensing techniques at short–medium term.

Published
2019

33. Monitoring phenology of crops at the parcel scale : combining high and medium spatial resolution data

Author

Rivas, Henry, Delbart, Nicolas, Ottle, Catherine, Maignan, Fabienne, Vaudour, Emmanuelle, Université Paris Diderot - Paris 7 (UPD7), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris Saclay (COmUE), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV]Life Sciences [q-bio], [SDE]Environmental Sciences
Abstract

International audience; Remotely-sensed vegetation phenology is used here to identify key stages of annual crop development and, in this basis, as an indicator of annual crop type. Crop monitoring requires both high spatial resolution data (HSR) for observing within sub-parcel scale, and high temporal resolution (HTR) to monitor vegetation changes during along the crop cycle. However, these simultaneous requirements are difficult to fulfill by the same satellite. In temperate areas such as the Versailles Plain, near Paris, France, HRS data have at best a dozen images exploitable per year, even with Sentinel-2 because of cloud cover, while those with medium spatial resolution (MRS) provide daily images, but at the generally mixed pixel scale. In France, the Land Parcel Identification System (LPIS) is an information system of the crop types declared by farmers, providing reference information about the annual crops cultivated within each agricultural parcel. In this work, the objective was to monitor the phenology of annual crops recorded in the LPIS of 2016, using satellite image time series from HRS Sentinel-2 (10m) and MRS Proba-V (100m) acquired from early to end of 2016 over the Versailles Plain, a small agricultural region (221 km2) cultivated with annual crops. From the two types of time series, the temporal variations of vegetation indices (NDVI / EVI2) of crops were extracted in order to analyze the crop seasonal variations of winter wheat, winter oilseed rape and maize over 2857 parcels with average size of 6.88 ha. The linear method of spatial disaggregation was applied on the MRS data, using fractions of each crop type in the mixed pixels calculated from the 2016-LPIS. The temporal responses from HRS data were compared with those of the MRS sub-pixels. Comparisons between both time series revealed significant correlations for the three studied crops (winter wheat = 0.94, winter oilseed rape = 0.74 and maize = 0.79). By improving the temporal frequency of the monitoring, from13 images for HRS to 25 images for MRS, the disaggregated MRS time series enabled to distinguish the phenological stages of the three studied crops better than the HRS time series. In conclusion, our method of spatial disaggregation can be used to improve the exploitation of satellite data at MRS in seasonal crop monitoring, especially during the transition periods when the spectral indices of crops are likely to change quickly.

Published
2019

34. Remote sensing data integration for soil clay content prediction at a national scale

Author

Loiseau, Thomas, Chen, Songchao, Mulder, Vera Leatitia, Roman Dobarco, Mercedes, Richer-de-Forges, Anne C, Lehmann, Sébastien, Bourennane, Hocine, Saby, Nicolas, Martin, Manuel, Vaudour, Emmanuelle, Gomez, Cécile, Lagacherie, Philippe, Arrouays, Dominique, InfoSol (InfoSol), Institut National de la Recherche Agronomique (INRA), Soil Geography and Landscape Group, Wageningen University and Research [Wageningen] (WUR), Unité de recherche Science du Sol (USS), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
[SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

35. Approches de zonage viticole fondées sur la télédétection.: Apport particulier de la télédétection des sols

Author

Vaudour, Emmanuelle, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), and Institut National de la Recherche Agronomique (INRA)-AgroParisTech

Subjects
[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study
Abstract

International audience; Cet article répertorie les approches de télédétection qui ont été développées à des fins de zonage viticole depuis la fin des années 1990. Il explicite la spécificité du zonage viticole et les enjeux sous-jacents au développement des techniques géospatiales pour les besoins de gestion géographique du vignoble. La télédétection offre un moyen puissant de réalisation et de mise à jour des zonages viticoles, en vue d'une telle gestion technique. Les résultats de zonage par télédétection sont d'autant plus pertinents, qu'ils sont combinés à d'autres types de mesures, telles que proxydétection des sols ou de la végétation de la vigne, ainsi que prospection pédologique conventionnelle, et reposent sur des jeux de données de référence, ainsi que des jeux de validation viticole, recueillis sur le terrain. La contribution de la télédétection à la cartographie des propriétés de sols viticoles est prometteuse au sein d'approches de cartographie numérique des sols.

Published
2019

38. Topsoil organic carbon modelling using jointly different sources

Author

zaouche, Mounia, Bel, Liliane, Tressou, Jessica, Vaudour, Emmanuelle, Mathématiques et Informatique Appliquées (MIA-Paris), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), and Institut National de la Recherche Agronomique (INRA)-AgroParisTech

Subjects
modelling, [SDV]Life Sciences [q-bio], Topsoil organic carbon
Abstract

Topsoil organic carbon modelling using jointly different sources. 9. Workshop on Spatiotemporal Modeling

Published
2018

39. Predicting key agronomic soil properties with fluorescence spectroscopy combined with reflectance spectroscopy: a farm-scale study in a Mediterranean viticultural agroecosystem

Author

Vaudour, Emmanuelle, Cerovic, Zoran G., Ebengo, Dav M., Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris Saclay (COmUE), Université Paris-Sud - Paris 11 (UP11), and Förderverein Uni Kinshasa

Subjects
[SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

40. Potential of combined Sentinel-1 / Sentinel-2 images for mapping topsoil organic carbon content over cropland taking into account soil roughness

Author

Ebengo Mwampongo, Dav, Vaudour, Emmanuelle, Gilliot, J.M., Hadjar, Dalila, Baghdadi, N., Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS), and Irstea Publications, Migration

Subjects
[SDE] Environmental Sciences, SENTINEL-1, SENTINEL-2, AGRICULTURAL AREA, [SDE]Environmental Sciences, NEURAL NETWORK
Abstract

International audience; Soil fertility management and climate change mitigation require the monitoring of soil organic carbon content. This study aimed at assessing the potential of combining Sentinel-1/Sentinel-2 images for topsoil organic carbon content (SOC) prediction over croplands, taking into account the soil surface roughness shaped by cultural operations. It focused on the Versailles plain, a peri-urban region of 221 Km2 located in the Ile-de-France region. Non-agricultural areas were masked using a vector layer derived from the graphical plot reference frame (RPG). Multispectral optical data were acquired from the European Space Agency (ESA) Sentinel-2 mission at four different dates in March-April 2017. For predicting SOC values, 129 plots sampled between 2010 and 2017, which were bare at the time of acquisitions, were used to construct Partial least squares regression (PLSR) models from the reflectance spectra of each Sentinel-2 image. In addition, a set of 13 Sentinel-1 radar images acquired in VH cross polarization and VV copolarization in dry condition during the same period were radiometrically calibrated, orthorectified and filtered by box filtering; they were then used to predict soil roughness from regression models based on soil roughness measurements (standard deviation of the surface height (Hrms)) at 40 plots sampled 3-4 times during a synchronous field campaign in March-April 2017. PLSR models of SOC prediction were constructed by separating plots according to their roughness level, being either smooth (Hrms < 2 cm) or rough (> 2 cm). The best prediction of soil roughness was obtained by inverting logarithmic regression obtained from radar backscattering on VH polarization and Hrms (Residual Prediction Deviation (RPD) of external validation 1.88; R2 of external validation 0.71). Separation of optical data according to their roughness level, resulted in a better predictive ability of SOC for smooth soils (R2 of Leave one-out cross validation (R2CV) 0.54, cross-validation RPD (RPDCV) 1.44) compared to rough (R2CV 0.39, RPDCV 1.3). At the four optical data acquisition dates, different performances were obtained (R2CV varying between 0.38 and 0.59). The best performance was for 9 April, when the seedbed was prepared for most plots (RMSECV = 1.2 g/Kg ; RPDCV 1.59). Effects of soil moisture, crop residues and emergent vegetation are here discussed, paving the way for a multidate approach for optimizing soil organic carbon content prediction over croplands.

Published
2018

41. Modélisation spatiale multi-sources du carbone organique dans le sol

Author

zaouche , Mounia, Bel , Liliane, Tressou , Jessica, Vaudour , Emmanuelle, Mathématiques et Informatique Appliquées (MIA-Paris), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Université Paris-Saclay, AgroParisTech-Institut National de la Recherche Agronomique (INRA), Université Paris Saclay (COmUE), Mathématiques et Informatique Appliquées ( MIA-Paris ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes ( ECOSYS ), AgroParisTech-Institut National de la Recherche Agronomique ( INRA ), and Université Paris Saclay

Subjects
Statistique spatiale, sol, [ SDV ] Life Sciences [q-bio], Spatial statistics, [SDV]Life Sciences [q-bio], INLA, joint modelling, SOC, carbone, modélisation jointe, SPDE
Abstract

In order to reduce chemical fertilizer in agricultural use and to value the urban organic matter in substitution, a precise knowledge of soil properties is mandatory. Carbon is a good indicator of soil fertility and having at our disposal a precise mappingof its content is useful. In this study we aim at spatially estimate the soil carbon content (SOC) in the Versailles plain and the Alluets plateau, a 220 km2 agricultural area. The novel Bayesian inference approach called Integrated Nested Laplace Approximation with Stochastic Partial Differential Equation (INLA-SPDE) allows us to ensure consistency between the various available sources of information (soil samples and satellite image) and to produce in a short time a posteriori estimations of the parameters and the SOC field, considered as a latent field. Several models were evaluated and compared using the elevation covariate stemming from a Digital Elevation Model (DEM), including or not the data from the satellite image. Adding the image slightly improves the prediction quality in terms of RMSE (Root Mean Square Error RMSE) since the median goes from 3.17 g.kg−1 to 3.15 g.kg −1. Overall the carbon prediction map from the joint model represents more realistically the spatial structure of the carbon field.; La réduction des intrants chimiques d’usage agricole et la valorisatition des mati`eres organiques d’origine urbaine en substitution nécessitent une connaissance fine des propriétés des sols agricoles. Le carbone étant un bon indicateur de la fertilité des sols, il s’avère nécessaire de disposer d’une cartographie précise des teneurs. Dans cette étude, on cherche à produire une cartographie des teneurs en carbone dans la plaine de Versailles et le plateau des Alluets, région agricole de 220 km2. La nouvelle approche d’inférence Bayesienne Integrated Nested Laplace Approximation et Stochastic Partial Differential Equation (INLA-SPDE) nous permet de mettre en cohérence les différentes sources d’information disponibles (prélèvements au sol et image satellite) et d’obtenir en peu de temps des estimations a posteriori des paramètres et du champ de carbone considéré comme un champ latent. Nous avons évalué et comparé via une procédure bootstrap les performances plusieurs modèles utilisant comme covariable l’altitude issue d’un modèle numérique de terrain incluant ou non les données des images satellites.L’intégration de l’image améliore légèrement la qualité de prédiction en terme de RMSE (Root Mean Square Error) dont la médiane passe de 3.17 g.kg−1 `a 3.15 g.kg−1. Mais surtout la carte de prédiction du carbone issue de la modélisation jointe présente de façon beaucoup plus réaliste la structure spatiale du carbone.

Published
2018

42. Extraction automatique du parcellaire agricole à partir d’images de télédétection et du registre parcellaire graphique sous QGIS/OTB

Author

Gilliot, Jean-Marc, Le Priol, Camille, Vaudour, Emmanuelle, Martin, Philippe, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, AgroParisTech, and Sciences pour l'Action et le Développement : Activités, Produits, Territoires (SADAPT)

Subjects
systèmes d'information géographiques, rpg explorer, [SDV]Life Sciences [q-bio], registre parcellaire graphique, sig, database, agriculture
Abstract

Chapitre 3; Extraction automatique du parcellaire agricole à partir d’images de télédétection et du registre parcellaire graphique sous QGIS/OTB

Published
2018

43. Predicting Key Agronomic Soil Properties with UV-Vis Fluorescence Measurements Combined with Vis-NIR-SWIR Reflectance Spectroscopy: A Farm-Scale Study in a Mediterranean Viticultural Agroecosystem

Author

Vaudour , Emmanuelle, Cerovic , Zoran, Ebengo Mwampongo , Dav, Latouche , Gwendal, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris-Saclay, Ecologie Systématique et Evolution (ESE), Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes ( ECOSYS ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Université Paris Saclay, Ecologie Systématique et Evolution ( ESE ), and Université Paris-Sud - Paris 11 ( UP11 ) -AgroParisTech-Centre National de la Recherche Scientifique ( CNRS )

Subjects
[ SDV ] Life Sciences [q-bio], soil properties, [SDV]Life Sciences [q-bio], partial least squares regression, model averaging, fertility assessment, Mediterranean vineyard soils, UV-Vis fluorescence, Vis-NIR-SWIR reflectance spectroscopy, multiple excitation fluorescence sensor
Abstract

For adequate crop and soil management, rapid and accurate techniques for monitoring soil properties are particularly important when a farmer starts up his activities and needs a diagnosis of his cultivated fields. This study aimed to evaluate the potential of fluorescence measured directly on 146 whole soil solid samples, for predicting key soil properties at the scale of a 6 ha Mediterranean wine estate with contrasting soils. UV-Vis fluorescence measurements were carried out in conjunction with reflectance measurements in the Vis-NIR-SWIR range. Combining PLSR predictions from Vis-NIR-SWIR reflectance spectra and from a set of fluorescence signals enabled us to improve the power of prediction of a number of key agronomic soil properties including SOC, Ntot, CaCO3, iron, fine particle-sizes (clay, fine silt, fine sand), CEC, pH and exchangeable Ca2+ with cross-validation RPD ≥ 2 and R² ≥ 0.75, while exchangeable K+, Na+, Mg2+, coarse silt and coarse sand contents were fairly predicted (1.42 ≤ RPD < 2 and 0.54 ≤ R² < 0.75). Predictions of SOC, Ntot, CaCO3, iron contents, and pH were still good (RPD ≥ 1.8, R² ≥ 0.68) when using a single fluorescence signal or index such as SFR_R or FERARI, highlighting the unexpected importance of red excitations and indices derived from plant studies. The predictive ability of single fluorescence indices or original signals was very significant for topsoil: this is very important for a farmer who wishes to update information on soil nutrient for the purpose of fertility diagnosis and particularly nitrogen fertilization. These results open encouraging perspectives for using miniaturized fluorescence devices enabling red excitation coupled with red or far-red fluorescence emissions directly in the field.

Published
2018

46. The potential of UAS imagery for soil mapping at the agricultural plot scale

Author

Gilliot, Jean-Marc, Michelin, Joël, Becu, Maxime, Cissé, Moustapha, Hadjar, Dalila, Vaudour, Emmanuelle, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, and DEFISOL

Subjects
[SDV]Life Sciences [q-bio]
Abstract

The potential of UAS imagery for soil mapping at the agricultural plot scale. EGU 2017, European Geophysical Union General Assembly 2017

Published
2017

47. Potential of SENTINEL-2 images for predicting common topsoil properties over Temperate and Mediterranean agroecosystems

Author

Vaudour, Emmanuelle, Gomez, Cécile, Fouad, Youssef, Gilliot, Jean-Marc, Lagacherie, Philippe, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Sol Agro et hydrosystème Spatialisation (SAS), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut de Recherche pour le Développement (IRD [ Madagascar])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, and Institut de Recherche pour le Développement (IRD)-Institut de Recherche pour le Développement (IRD [ Madagascar])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

Potential of SENTINEL-2 images for predicting common topsoil properties over Temperate and Mediterranean agroecosystems. EGU 2017, European Geophysical Union General Assembly 2017

Published
2017

48. Retracing recurring vine mortality patterns over a long duration: case study of a Mediterranean viticultural estate

Author

Vaudour, Emmanuelle, Leclercq, Léa, Gilliot, Jean-Marc, Chaignon, Benoît, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), and Institut National de la Recherche Agronomique (INRA)-AgroParisTech

Subjects
[SDV]Life Sciences [q-bio]
Abstract

Retracing recurring vine mortality patterns over a long duration: case study of a Mediterranean viticultural estate. EGU 2017, European Geophysical Union General Assembly 2017

Published
2017

49. Soil and culture viewed through the prism of viticultural terroir

Author

Vaudour, Emmanuelle, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), and Institut National de la Recherche Agronomique (INRA)-AgroParisTech

Subjects
[SDV]Life Sciences [q-bio]
Abstract

Soil and culture viewed through the prism of viticultural terroir. EGU 2017, European Geophysical Union General Assembly 2017

Published
2017

50. Combining optical remote sensing, agricultural statistics and field observations for culture recognition over a peri-urban region

Author

Delbart, Nicolas, Vaudour, Emmanuelle, Maignan, Fabienne, Ottlé, Catherine, Gilliot, Jean-Marc, Pôle de recherche pour l'organisation et la diffusion de l'information géographique (PRODIG), Université Paris 1 Panthéon-Sorbonne (UP1)-Institut de Recherche pour le Développement (IRD)-Université Paris-Sorbonne (UP4)-AgroParisTech-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Pôle de recherche pour l'organisation et la diffusion de l'information géographique ( PRODIG ), Centre National de la Recherche Scientifique ( CNRS ) -Université Panthéon-Sorbonne ( UP1 ) -AgroParisTech-Université Paris-Sorbonne ( UP4 ) -Institut de Recherche pour le Développement ( IRD ) -Université Paris Diderot - Paris 7 ( UPD7 ), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes ( ECOSYS ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] ( LSCE ), Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Université Paris Diderot - Paris 7 (UPD7)-Institut de Recherche pour le Développement (IRD)-Université Paris-Sorbonne (UP4)-AgroParisTech-Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)

Subjects
Peri-urban region, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, [SPI]Engineering Sciences [physics], [ SDV ] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], Optical remote sensing, [ SPI ] Engineering Sciences [physics], Agricultural statistics, [ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2017

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