Weather data publication on the LOD using SOSA/SSN ontology

International audienceThis paper presents an RDF dataset of meteorological measurements. The measurements come from one weather station at the Irstea experimental farm located in Montoldre. The measurements have been made from August 2018 until now. They have been transformed and published as Linked Open Data (LOD). The data schema is based on the new version of the Semantic Sensor Network ontology. This ontology version integrates the Sensor, Observation, Sample, and Actuator pattern. We first present the network of ontologies used to organize the data. Then, the transformation process for publishing the dataset is detailed. To conclude we present some use cases of queries related to Irstea research projects. © 2020 - IOS Press and the authors

Design and optimization of a polarization imaging system independent of intensity fluctuations (Orale)

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Semi-supervised contrast enhancement in polarimetric images using non-parametric statistical snake (Orale)

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Le Challenge ROSE (2018–2021) : évaluation itérative d’approches de recherche parallèles pour le désherbage intra-rang.

En 2017, les ministères chargés de l’agriculture et de la transition écologique ont lancé, en partenariat avec le ministère chargé de la recherche et l’Agence Nationale de la Recherche (ANR), un appel à projets «Challenge ROSE». Il s’agit de susciter la mise au point de solutions technologiques innovantes permettant de contribuer à atteindre les objectifs du plan Ecophyto II : réduire l’utilisation des produits phytopharmaceutiques, garantir une meilleure maîtrise de l’ensemble des risques et diminuer la dépendance de l’agriculture à ces produits. Les projets retenus sont focalisés sur le désherbage de l’intra-rang (espacement entre plants sur une même rangée) en cultures légumières de plein champ et en grandes cultures à fort écartement. L’ensemble de la chaîne d’intervention est pris en compte (observation et détection des cultures et des mauvaises herbes, interprétation, action de désherbage) grâce à des avancées scientifiques dans plusieurs domaines : les capteurs, la modélisation, la robotique et leur combinaison. Les équipes participantes disposent d’une parcelle de l’AgroTechnoPôle sur le site de l’Irstea à Montoldre dans l’Allier. Durant quatre ans, ces équipes vont se confronter chaque année à des épreuves réelles de terrain. L’efficacité du désherbage, dans le respect des cultures en place, sera l’objet des campagnes d’évaluation annuelles menées par le LNE et Irstea, avec la participation de VetAgro Sup.In 2017, the Ministries of agriculture and ecological transition launched, in partnership with the Ministry of Research and the French National Research Agency (ANR), the call for research proposals “ROSE Challenge”. The aim is to encourage the development of innovative technological solutions to help achieve the objectives of the Ecophyto II plan: reducing the use of plant protection products at least by half, ensuring better control of all risks and reducing agriculture’s dependence on chemicals. The research teams of the selected projects will focus on intra-row weeding (intra row: spacing between plants in the same row) in field vegetable crops and wide-spaced field crops (i.e. maize, sunflower).[br/] The entire chain of action will be taken into account (observation and detection of crops and weeds, interpretation, weeding) thanks to scientific advances in several fields: sensors, modelling, robotics and their combination. The research teams will have a plot of land belonging to the AgroTechnoPôle at the Irstea site in Montoldre, France. For 4 years, these teams will be confronted with real field events. The effectiveness of weeding, while respecting existing crops, will be the subject of annual evaluation campaigns conducted by the LNE and Irstea, with the participation of VetAgro Sup

PREDICTION OF A WHEAT CROP YIELD MAP BY USING POST-ANTHESIS RADIOMETRICAL DATA

International audienceBecause yield maps provide only synthetic information on the whole crop cycle, it appears necessary to supplement them with more analytical tools enabling to explain the spatial variations in measured yield and to make diagnosis. Here we tested two candidate methods: simulation modelling and radiometric mapping of green leaf area index (GLAI) after anthesis, on a 15-ha wheat-cropped field with marked soil and topographic heterogeneity under a temperate climate. When aggregated over the major soil units within the field, GLAI maps and modelling could mimic their overall effects on yield. However, they both were poor predictor of short-range (10 m) yield variability, even when the model was re-initialized with the GLAI data measured after anthesis. Possible reasons include sampling and spatial joint biases, and that GLAI should be taken several times during grain filling

Une architecture SOLAP basé sur les capteurs et un outil ACV

International audienceAgricultural energy consumption is an important environmental and social issue. Several diagnosis tools have been proposed to define indicators for analyzing the large-scale energy consumption of agricultural farm activities (year, farm, production activity, etc.). In Bimonte, Boulil, Chanet and Pradel (2012), the authors define (i) new appropriate indicators to analyze agricultural farm energy-use performance on a detailed scale and (ii) show how Spatial Data Warehouse (SDW) and Spatial OnLine Analytical Processing (SOLAP) GeoBusiness Intelligence (GeoBI) technologies can be used to represent, store, and analyze these indicators by simultaneously producing graphical and cartographic reports. These GeoBI technologies allow for the analysis of huge volumes of georeferenced data by providing aggregated numerical values visualized by means of interactive tabular, graphical, and cartographic displays. However, existing data collection systems based on sensors are not well adapted for agricultural data. In this paper, the authors show the global architecture of our GeoBI solution and highlight the data collection process based on agricultural ad hoc sensor networks, the associated transformation and cleaning operations performed by means of Spatial Extract Transform Load (ETL) tools, and a new implementation of the system using a web-services-based loosely coupled SOLAP architecture to provide interoperability and reusability of the complex multi-tier GeoBI architecture. Moreover, the authors detail how the energy-use diagnosis tool proposed in Bimonte, Boulil, Chanet and Pradel (2012) theoretically fits with the sensor data and the SOLAP approach

Irstea Use Case: Integration of crop observations using semantic web technologies

International audiencePrésentation of AgroTechnopole where Irstea develops a use case of data integration of Crop observation.Présentation de l'agro technopole où Irstea développe un cas d'utilisation d'intégration des données de culture