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International audience; As we move towards shipboard-underway and automated systems for monitoring water quality and assessing ecological status, there is a need to evaluate how effective the existing monitoring systems are, and how we could improve them. Considering the existing limitations for processing numerous and complex data series generated from automated systems, and because of processes involved in phytoplankton blooms, this paper proposes a data-driven evaluation of an unsupervised classifier to optimize the way we track phytoplankton, including harmful algal blooms (HABs), and to identify the main associated hydrological conditions. We used in situ data from a portable flow-through automatic measuring system coupled with a multi-fixed-wavelength fluorometer implemented in the eastern English Channel during a bloom of Phaeocystis globosa (high biomass, non-toxic HAB species). This combination of technologies allowed high resolution online hydrographical and biological measurements, including spectral fluorescence as a means of quantifying phytoplankton biomass and simplifying the phytoplankton community structure inference. An unsupervised spectral clustering method was applied to this multi-parameter high-resolution time series, which allowed discrimination under near real-time of 6 to 33 contrasting water masses based on their abiotic and biotic characteristics. In addition, areas subject to extreme events such as HABs could be precisely identified, so controlling factors or their direct and indirect effects could be hierarchized. Considering the benefits and limitations of such a strategy, future applications of such methods will be important in the context of implementing the Marine Strategy Framework Directive.

International audience; In aquaculture, management practices such as supplementary feeding or fertilisation of water are gen- erally considered to improve fish yield in ponds or shallow lakes. Nevertheless, in semi-natural systems where many ponds or lakes are situated in a cultural landscape, this is much less evident for certain fish farmers because fish production systems are often quite extensive, and fish production is only one economic activity among others for these fish farmers. In this paper we analyse the influence of different management practices on fish yield and nutrient status of fish ponds' water and sediments, and we have an additional regard on potential implications of this in the perspective of the European Water Frame- work Directive. This directive demands that artificial water bodies such as fish ponds have to attain a good ecological potential in 2015, and thus to adapt water body management to achieve this. In total, 83 fish ponds were studied from 2007 to 2009 in the Dombes region, France. This region is characterised by 1100 nutrient rich fish ponds located in a heterogeneous agricultural landscape with cropping, animal husbandry and forestry. Different water parameters (PO4 3− , NO3 − , total P, total N, NH4+ , chlorophyll-a) were analysed from April to October in each year. Sediments were sampled in March and October and analysed for available P, total N, organic matter and Ca concentration. Data about pond management practices such as fertilisation of pond water, supplementary feeding as well as fertilisation and liming of pond grounds when they are emptied and let dried out during a year, and harvested fish were collected by interviewing pond owners and pond managers. The main results found are that the combination of the annual management practices supplementary feeding and fertilisation, increased significantly the fish yields. When combining the annual with the non-annual management practices fertilisation of pond grounds and liming of pond grounds during a year when ponds are emptied, highest yield were obtained. Using only the non-annual practices, yields could be positively influenced. Lowest yields were found when no management practice was applied. Significant, but contrasting effects of pond management practices on water or sediment parameters were only found for available P of sediments and NO3− for the management practices supplementary feeding, fertilisation of water, or liming of the pond ground. Whereas available P of sediments showed higher values with the three practices, NO3− in the water showed lower values. Although only few significant differences were found, means of parameters showed a certain trend as they were in many cases, besides for total N and NO3−, higher with the management practice. Our results show that there is a limited effect of pond management practices on the chemical status of the pond water and sediments. This also suggests a limited potential to change management practices to respond to the demand of the European Water Framework Directive for good water quality and ecological potential.

International audience; In this paper, we present an optimized Machine Learning (ML) algorithm for predicting land suitability for crop (sorghum) production, given soil properties information. We set-up experiments using Parallel Random Forest (PRF), Linear Regression (LR), Linear Discriminant Analysis (LDA), KNN, Gaussian Naïve Bayesian (GNB) and Support Vector Machine (SVM). Experiments were evaluated using 10 cross fold validation. We observed that, parallel random forest had a better accuracy of 0.96 and time of execution of 1.7 sec. Agriculture is the main stream of food security. Kenya relies on agriculture to feed its population. Land evaluation gives potential of land use, in this case for crop production. In the Department of Soil Survey in Kenya Agriculture and Livestock Research Organization (KALRO) and other soil research organizations, land evaluation is done manually, is stressful, takes a long time and is prone to human errors. This research outcomes can save time and improve accuracy in land evaluation process. We can also be able to predict land suitability for crop production from soil properties information without intervention of a soil scientist expert. Therefore, agricultural stakeholders will be able to efficiently make informed decisions for optimal crop production and soil management.

The works focus on the identification of industrial robots that belongs to the field of the identification of continuous-time inverse dynamic models in closed loop. First, a generic instrumental approach relevant for the identification of rigid industrial robots is proposed. The set of instruments is the inverse dynamic model constructed from simulated data calculated from the simulation of the direct dynamic model. This algorithm termed the IDIM-IV method validates the inverse and direct dynamic models simultaneously, improves the noise immunity of estimates with respect to corrupted data in the observation matrix and has a rapid convergence. This new approach is experimentally validated and compared with other standard methods. Then, a statistical test able to assess the validity of the set of instruments as well as the consistency of the least-squares estimates is presented. This test is based on the use of the Two-Stage-Least-Squares method and the regressed Durbin-Wu-Hausman test that are commonly used in econometrics. Finally, the perspectives that the IDIM-IV method can offer to the communities of robotics and automatic control are enlightened Ce manuscrit résume les travaux menés sur l'identification des robots industriels conduits à l'ONERA. Dans le premier chapitre, les méthodes usuelles de modélisation et d'identification appliquées aux robots industriels rigides sont présentées. Le deuxième chapitre introduit une nouvelle méthode d'identification basée sur l'utilisation des variables instrumentales alors que le troisième chapitre présente un test statistique capable de valider la construction des instruments. Enfin, dans un quatrième chapitre, les perspectives offerts par ces nouvelles méthodes sont introduites.

International audience; During the Vietnam War, South-Vietnam underwent numerous herbicides spraying and bombing, which were conducted by the American army. These military activities aimed to defeat the enemy by destroying its environment; thus they were not without consequences on landscapes. As prime target of aerial attacks, the forests were particularly affected. The Vietnam War can thus be considered as a cause of forest loss but not the main one. Some assert that the areas affected by the military practices were forested before the war and the forest disappeared due to these ones; but did it correspond to the reality? To answer, to identify as objectively as possible the landscape dynamics, which occurred during the war, Thua Thien Hue province, particularly affected by the military practices, is taken as an example; its pre- (circa 1954) and post-war (1975) landscapes have to be reconstructed, basing on a priori unbiased data such as iconographic data. Aerial photographs are available for circa 1954 but the reconstruction can only be partial because some are missing and their processing is long. For 1975, another iconographic data is used, a satellite image; available, it has the advantage of covering the studied province and of requiring a shorter processing. The pre- and post-war landscapes thus known are then compared to identify wartime dynamics. This study demonstrates that some forests were destroyed but other sylvo-ecosystems progressed as well. Besides the military activities, the civilian practices were factors of these dynamics.

International audience; The limited availability of soil information has been recognized as a main limiting factor in digital soil mapping (DSM) studies. It is therefore important to optimize the joint use of the three sources of soil data that can be used as inputs of DSM models, namely spatial sets of measured sites, soil maps and soil sensing products.In this paper, we propose to combine these three inputs, through a cokriging with a categorical external drift (CKCED). This new interpolation technique was applied for mapping seven soil properties over a 24.6 km2 area located in the vineyard plain of Languedoc (Southern France), using an hyperspectral imagery product as example of a soil sensing data. Cross-validation results of CKCED were compared with those of five spatial and non-spatial techniques using one of these inputs or a combination of two of them.The results obtained in the La Peyne Catchment showed i) the utility of soil map and hyperspectral imagery products as auxiliary data for improving soil property predictions ii) the greater added-value of the latter against the former in most situations and iii) the feasibility and the interest of CKCED in a limited number of soil properties and data configurations. Testing CKCED in case study with soil maps of better quality and soil sensing techniques covering more area and depths should be necessary to better evaluate the benefits of this new technique.

International audience; It has been 35 years since Igbozurike and Raza (1983), and rural communities in Nigeria continue to face many of the challenges identified in the ARMTI seminar. Poverty and rural-urban migration remain widespread in Nigeria. Further issues of security and terrorism have also made their way into the array of problems facing rural communities in Nigeria. Therefore, the aim of this paper is to review the issues affecting the quality of life in 21st century rural Nigeria, in order to ascertain what has changed or remained the same since 1983. In achieving the study aim, the parameters used by Igbozurike and Raza (1983) will be linked with current literature on the quality of life in rural Nigeria. The paper will look at the following parameters: socioeconomic indicators, social services and infrastructure, nutritional status, population structure and mobility, institutional frameworks and the role of Agricultural Development Projects (ADPs).

Grasp planning and most specifically the grasp space exploration is still an open issue in robotics. This article presents a data-driven oriented methodology to model the grasp space of a multi-fingered adaptive gripper for known objects. This method relies on a limited dataset of manually specified expert grasps, and uses variational autoencoder to learn grasp intrinsic features in a compact way from a computational point of view. The learnt model can then be used to generate new non-learnt gripper configurations to explore the grasp space. accepted at SYSID 2021 conference

Abstract The carbon and land footprint of 26 certified food products – geographical indications and organic products and their conventional references are assessed. This assessment goes beyond existing literature by (1) designing a calculation method fit for the comparison between certified food and conventional production, (2) using the same calculation method and parameters for 52 products – 26 Food Quality Schemes and their reference products – to allow for a meaningful comparison, (3) transparently documenting this calculation method and opening access to the detailed results and the underlying data, and (4) providing the first assessment of the carbon and land footprint of geographical indications. The method used is Life Cycle Assessment, largely relying on the Cool Farm Tool for the impact assessment. The most common indicator of climate impact, the carbon footprint expressed per ton of product, is not significantly different between certified foods and their reference products. The only exception to this pattern are vegetal organic products, whose carbon footprint is 16% lower. This is because the decrease in greenhouse gas emissions from the absence of mineral fertilizers is never fully offset by the associated lower yield. The climate impact of certified food per hectare is however 26% than their reference and their land footprint is logically 24% higher. Technical specifications directly or indirectly inducing a lower use of mineral fertilizers are a key driver of this pattern. So is yield, which depends both on terroir and farming practices. Overall, this assessment reinforces the quality policy of the European Union: promoting certified food is not inconsistent with mitigating climate change.

International audience; Marvejols is a small town located in Lozère (France). Traditionally, the region was poor with an agricultural oriented economy. However, by the 1960s a new type of business was launched: the residential care facilities for disabled people, especially in relation to Jacques Blanc, a key person in the organization and development of this business. This economic activity brought jobs and new attractiveness, counterbalancing decline in traditional sectors. Nevertheless, currently, situation is less favourable, and the local players try to find out a new strategy, particularly in relation to diversification. In this study, our main aim was to understand conditions of starting and growing of this business. Moreover, we would like to understand current fragilities and attempts to adapt the economy of the territory. In this way, our students and we have chosen this area in relation to the economic and historical weight of its activity. The organization of field trips and survey was conducted in a comprehensive approach perspective. Therefore, we took account parameters working in this territory, such as strategies, psychologies (individual and collective), networks and identities. Human dimensions are strong, especially in discourses, and our main result is a better understanding of the local situation, with comparisons to close cases (Corrèze, Creuse). Furthermore, the quality of the geographical analysis provides working relations with the stakeholders