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The aim of this paper is the development of an algorithm, based on expert knowledge, for the Land cover classification of an Italian Grassland Area. To accomplish this task, a dataset composed by 4 Worldiew-2 (WV-2) images, at 2 m of spatial resolution, has been considered. Despite their poor spectral resolution, Very High spatial Resolution (VHR) data allow the identification of individual objects by means of the information in the relationship between adjacent pixels, including texture and shape. For this reason a Geographic Object-Based Image Analysis (GEOBIA) approach consisting in a rule set based on the elicitation of expert rules concerning phenology, spatial features and agricultural practices in conjugation with prior spectral knowledge, has been used. The study area, of almost 500 kmq, is located in Southern Italy (Puglia Region) within the Natura 2000 "Alta Murgia" site (SCI/SPA IT9120007, according to Habitat Directive 92/43 and Bird Directive 147/2009), partly designated as a National Park as from 2004. Semi-natural dry grasslands cover almost 24% of the total area of the site which represent one of the most important areas for the conservation of this kind of ecosystems in Europe.

This paper focuses on the application of a semi-automatic unsupervised change detection algorithm called Cross Correlation Analysis (CCA) to the detection of (semi-) natural grasslands changes at Very High Resolution (VHR). A reference validated Land Cover/Land Use map at time T1 and only one satellite image at time T2, with T2>T1, are required to detect changes occurred at T2 in the selected target class. This approach offers the possibility to reduce the costs of change detection when the acquisition of multi-seasonal VHR images at time T2 for supervised change detection is too expensive or when no archive VHR image is available in the past for unsupervised comparison between T1 and T2 images. A summer Worldview-2 image for a Natura 2000 test site was considered and the results appear encouraging.

Camelina sativa (L.) Crantz, is an annual plant belonging to the Brassicaceae family, as rapeseed. It is native to central Europe where it was widely cultivated until the 1940s. However, only recently it gained the interest of the energy and bio-based industries as a low-cost non-food crop for aviation biofuel production and the oleochemical industry, due to its high oil content (up to 40%) and suitable oil profile. Field trials are performed at different locations in Europe, to study the effect of sowing dates on camelina seed and oil yields, in three different environments, the South (Greece) and North Mediterranean (Italy) climatic zones as well as the Continental zone (Poland). The activity was organized in two separate experiments: autumn sowing and spring sowing with two camelina varieties: Midas, a spring variety supplied by Linnaeus Plant Science (Canada), and Luna, a commercial winter variety from Poland. Total biomass ranged between 2.8 – 9.8 Mg DM ha-1, depending on the site and sowing seasons, with the highest figures in Italy and the lowest in Greece. Seed yields ranged from 0.56 – 2.11 Mg DM ha-1, depending on the site and sowing seasons, with the highest figures in the mild Mediterranean environments. Likewise, oil content ranged between 36.50 – 40.55%. Winter camelina reached almost double the seed yield compared to the spring crop for the same spring variety, Midas. Autumn sowing was found more productive than spring sowing for seed yields and oil content both in Greece and Italy, while in Poland, only real winter camelina varieties survive winter. Proceedings of the 26th European Biomass Conference and Exhibition, 14-17 May 2018, Copenhagen, Denmark, pp. 133-135

The Souss-Massa region, located in the south-west of Morocco, is among the regions that suffer the most from water stress. It’s characterized by an arid climate with low and irregular rainfall in time and space. Consequently, there’s a considerable rainfall deficit which negatively affects the water resources in the region. Moreover, the economy of the region is mainly based on agriculture which consumes more than 90% of the region's total water resources. As a result, surface water resources have become increasingly insufficient with regard to the demand. Use of groundwater resources has always been a secular practice in the area. In recent years, groundwater overexploitation has exceeded the renewable resources and has led to the depletion of the different aquifers of Souss-Massa region. In addition, high population growth, degradation of water quality, expansion of agricultural and industrial activity negatively affected water availability. Furthermore, a significant proportion of raw industrial and urban water rejections are released directly into nature, and excessive use of pesticides in agriculture and marine intrusion cause pollution and salinity of the groundwater. This study focuses on the vulnerability of groundwater resources and alternative solutions for agricultural development. This thematic allows the use of unconventional waters to test new techniques for the treatment and recycling of wastewater. Treated wastewater will be reused for irrigation in the Souss-Massa region, in order to reduce the vulnerability of water resources scarcity, to improve economic growth, to promote sustainable use of treated wastewater in agriculture and to produce good quality agricultural products.

International audience; To address the needs of the EU NoAW project, in this paper we solve the problem of efficiently generating the argumentation graphs from knowledge bases expressed using existential rules. For the knowledge bases without rules, we provide a methodology that allows to optimise the generation of argumentation graphs. For knowledge bases with rules, we show how to filter out a large number of arguments and reduce the number of attacks.

Disseminating and Promoting Smart Farming Technologies - The Smart AKIS Network Paper submmitted by Smart AKIS Network to 1st Conference AXEMA-EurAgEng, held in Paris on Feb. 25, 2107 This paper summarises the early stages of the Smart AKIS project which aims to collect and disseminate Smart Farming Technologies (SFT) in line with farmers’ needs. The methodology of collecting information and opinions from over 270 farmers from seven countries about SFTs is given. The methodology of collecting and analyzing the results of 718 scientific articles and 201 research projects to determine what the research topics and results are also outlined. Further information about the 164 SFT products that had been submitted by mid-January 2017 and entered into the inventory database are also summarized. There is outline information on how to submit research and product information to the inventory database on an on-going basis so that it can be promoted to end users (farmers, farming-advisors and contractors) and also seen by potential funders and collaborators for further product development and research collaboration which is also an objective of the Innovation Workshops which are starting in February 2017 around the seven countries.

International audience

Sustainable HCI scholars have shown a growing interest in augmenting with technology everyday devices for promoting energy conservation behaviors in different contexts of use. The workspace has not been sufficiently explored as space where everyday appliances and work equipment might be converted into persuasive devices which raise eco-awareness. In this paper, we present the design of persuasive IoT devices that help to promote energy-efficient behaviour change in the workplace. This approach issued by applying Grounded Theory analysis over qualitativedata collected at ten focus groups sessions after running a one year study where participants were treated to different persuasive strategies. With these data, five design categories emerged to be taken into account in the conception phase when devising tangible objects that aim toform pro-environmental behaviour change at workplaces. Our design-insights are also derived from an evaluation of the literature on ambient devices that encourage energy-efficient practices.