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Medium resolution satellite data, such as Sentinel-2 of the Copernicus programme, offer great new opportunities for the agricultural sector, and provide insights on soil surface characteristics and their management. Soil monitoring requires a high-quality dataset of uncovered and plastic covered agricultural soil. We developed a methodology to identify uncovered soil pixels in agricultural parcels during seedbed preparation and considered the impacts of clouds and shadows, vegetation cover, and artificial covers, such as those of greenhouses and plastic mulch films. We preserved the spatial and temporal integrity of parcels in the process and analysed spectral anomalies and their sources. The approach is based on freely available tools, namely Google Earth Engine and R Programming packages. We tested the methodology on the northern region of Belgium, which is characterised by small, fragmented parcels. We selected a period between mid-April to end-May, when active agricultural management practices leave the soil bare in preparation for the main cropping season. The spectral angle mapper was used to identify soil covered by non-plastic greenhouses or temporary soil covers, such as plastic mulch films. The effect of underlying soil on temporary covers was considered. The retrogressive plastic greenhouse index was used for detecting plastic greenhouses. The result was a high quality dataset of potential bare uncovered agricultural soil that allows further soil surface characterisation. This offered an improved understanding of the use of artificial covers, their spatial distribution, and their corresponding crops during the considered period. Artificial covers occurred most frequently in maize parcels. The approach resulted in precision values exceeding 0.9 for the detection of temporary covers and non-plastic greenhouses and a sensitivity value exceeding 0.95 for non-plastic and plastic greenhouses.

Climate change influences the frequency and intensity of extreme weather events, which have a strong impact on agroecosystems. At regional scale, agroecosystems are diverse in terms of ecological environment and farming practice, intrinsic properties that influence their vulnerability to such events. The link between extreme weather events and the vulnerability of agroecosystems can be conceptualized by experts, including farmers, advisers, and agricultural scientists. However, their knowledge is not easily taken into account in models. A transdisciplinary modeling approach was developed to map the vulnerability of agroecosystems based on expert knowledge using a combination of a fuzzy inference system and geographical information system. The developed approach was applied to assess the vulnerability of two major Belgian agroecosysems: (i) the vulnerability of cropland to heavy rain, and (ii) the vulnerability of grassland to drought. The approach is flexible and identifies the various factors underlying the vulnerability and provides a useful tool to study potential sources of adaptation and resilience within agricultural systems.

Spatial modelling of extreme dry (wet) spells is relevant to design agricultural insurances and establish risk management strategies. We characterised dry (wet) spells during the period 1971–2010 in 133 rainfall stations and investigated their impact on crop yields across Belgium. A day was considered as a dry (wet) day when the total amount of rainfall is below (above) 0.2 mm. A two-way ANOVA demonstrated significant differences between low and high yields across 12 agricultural regions in the number of consecutive dry (wet) days, rainfall amount during the wet days and their total during the crop growing season. Generalised Extreme Value distributions were fitted to the maxima series using maximum likelihood to estimate the distribution parameters. The number of consecutive dry (wet) days and rainfall amount was considered during the cropping season between March and October. We modelled maxima observed at rainfall stations by means of max-stable processes, an extension of multivariate extreme value theory. Spatial extreme modelling was performed through pairwise likelihood inference by a madogram and enabled 20-year return levels to be simulated across regions based on geographic coordinates and altitude as covariates. Spatial return levels confirmed the exceptionality of 2016 and 2018 as extreme wet and dry years with high return periods. The 2018 drought resulted in yield reductions of 74% for maize and 42% for potato, while the 2016 rainfall induced yield losses of up to 39% for winter cereals, 45% for maize and 53% for potato. The max-stable models provided a good fit to the joint behaviour of extremes in the number of consecutive dry (wet) days during the growing season as an indication for crop stress. The method allows for spatio-temporal characterisation of generalised extreme value distributions across regions, and provides a tool for weather based insurances and risk management.

Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper, we reviewed crowdsourcing initiatives in agricultural science and farming activities and further discussed the particular characteristics of this approach in the field of agriculture. On-going crowdsourcing initiatives in agriculture were analysed and categorised according to their crowdsourcing component. We identified eight types of agricultural data and information that can be generated from crowdsourcing initiatives. Subsequently we described existing methods of quality control of the crowdsourced data. We analysed the profiles of potential contributors in crowdsourcing initiatives in agriculture, suggested ways for increasing farmers’ participation, and discussed the on-going initiatives in the light of their target beneficiaries. While crowdsourcing is reported to be an efficient way of collecting observations relevant to environmental monitoring and contributing to science in general, we pointed out that crowdsourcing applications in agriculture may be hampered by privacy issues and other barriers to participation. Close connections with the farming sector, including extension services and farm advisory companies, could leverage the potential of crowdsourcing for both agricultural research and farming applications. This paper coins the term of farmsourcing as a professional crowdsourcing strategy in farming activities and provides a source of recommendations and inspirations for future collaborative actions in agricultural crowdsourcing.

The impact of climate change could undermine the future grain production as a consequence of increased temperature and drought condition or improve the crop performance owing to the increased CO2 in the atmosphere. Wheat water demand and yield are strictly related to climate conditions of the area where the plants are cropped. In this study, we assessed the future trends of grain yield and water consumption in two European regions, Germany (Continental region) and Italy (Mediterranean region) in the light of the multiple sources of uncertainty related to climate and yield forecasts. Four crop models were set up under combinations of two European climate regions, five Global Circulation Models and two Representative CO2 Concentration Pathways, 486 ppm and 540 ppm in 2050. Yield and water use were assessed under rainfed and irrigated regimes, and the water footprint of green water and total water was estimated. Our results indicated that projected yields were comparable (Mediterranean area) or even improved (+9%; Continental area) in rainfed conditions in comparison to the current trend; and water supply enhanced crop performance (+22% in Germany and +19% in Italy, as mean). Crop water consumption (both green and blue) remained stable in future projections but the water footprint was 5% lower on average in Italy and 23% in Germany when compared to the baseline. Despite the uncertainty in future predictions related to the factors analysed, our result indicated that current wheat production and its water footprint could become more favourable under climate change. ispartof: SCIENCE OF THE TOTAL ENVIRONMENT vol:658 pages:1186-1208 ispartof: location:Netherlands status: published

The link between climate change and desertification is an important global problem for the United Nations Framework Convention on Climate Change (UNFCCC) and the United Nations Convention to Combat Desertification (UNCCD). The coastal provinces in Southern Centre Vietnam are strongly influenced by desertification, which is further exacerbated by climate change. The Delphi method was used to select sustainability indicators and then a method of an analytical hierarchy process was applied to prioritize sustainable solutions in Binh Thuan experts to elicit the causes and effects of desertification. According to the panel of 23 experts, 27 cause (e.g. rainfall and sunshine duration) and 22 effect (e.g. rice and agriculture) indicators were of particular importance to desertification and drought in the province. The highest priorities for cause are given to emigration, followed by income from industry and water supply for household use. The highest priorities for effect in the area are given to socioec...

Poplar (Populus spp.) and willow (Salix spp.) short rotation coppice (SRC) are attractive feedstock for conversion to renewable electricity. Site managers typically optimize biomass production at their sites. However, maximum biomass production does not necessarily equate an optimal CO2 balance, water use and energy production. This is because many operational actions consume water and energy and emit CO2, either on-site or off-site. Coupling a land surface model (ORCHIDEE-SRC) with life cycle assessment enabled us to determine the optimal management for SRC in Belgium. We simulated 120 different management scenarios for each of two well-studied Belgian SRC sites (i.e. Boom and Lochristi). Simulated soil carbon changes suggested substantial carbon losses of 20–30 Mg ha−1 over a time period of 20 years, which were within observation-based uncertainty bounds. Results showed that in Belgium, which has a temperate maritime climate, optimal management of SRC has a rotation cycle of two years without irrigation. Energy inputs for this optimal management were 5.2 GJ ha−1 yr−1 for the Boom site and 5.3 GJ ha−1 yr−1 for the Lochristi site, while the biomass yields at Boom and Lochristi were 9.0 Mg ha−1 yr−1 and 9.4 Mg ha−1 yr−1, respectively. The energy ratio (i.e., ratio of bioelectricity output to cumulative energy input) for this optimal management was 12, on average. Planting density turned out to be unimportant, while rotation length turned out to be most important to obtain the highest energy ratio and still maintain high biomass yield. Scenarios with high energy-input generated more bioenergy outputs, but the energy gains did not compensate for the increased energy inputs. Reductions in energy consumption per unit of bioenergy output should target the agricultural stage since it accounted for the largest energy share in the production chain.

Few studies have addressed the topic of farmers' adaptation to climate change from a multidisciplinary perspective, because of the difficulty in assessing their impacts. In view of the growing concern in the agricultural sector on this issue, we analyzed farm-level adaptation through arable land-use changes in the specific case of the Loam region in Belgium. With this aim, we used an agro-economic model which considered 20-year series of current and projected simulated yields with and without considering additional farming practices to reduce crop stress, such as irrigation and soil and water conservation techniques. Agronomic results show that climate change will negatively affect summer crop yields, particularly sugar beet and potatoes. However, we also show that adaptation to climate change through land-use changes can compensate for crop yield losses and lead to utility gains. These are obtained by reducing the share of land allocated to summer crops and barley and by increasing the surface allocated to less vulnerable crops such as winter wheat. Finally, irrigation practices would not be justified in the Loam region under climate change, since their use would incur important financial costs for farmers.

A new research project AFTER “Impacts of climate change and cli- mateextremesonAgricultureandForestryintheEurope-Russia-Turkey Region” started in 2018. It was designed to bridge the gap between supplyanddemandofstate-of-the-artclimateinformationtoassessthe impact of changing climate on agriculture and forestry.

WatchITGrow is a web-based application developed for potato monitoring in Belgium. The different components encompass a back-end with biophysical parameters derived from high resolution satellite imagery, agrometeorological algorithms, phenological development and crop models; and a front-end with dashboards to visualize spatio-temporal information and insert potato field information.

Vietnam is a coastal country projected to be heavily affected by climate change. Binh Thuan Province is part of the driest region of Vietnam and is prone to desertification. An expert panel participated in developing a Leopold matrix which allowed for identification of desertification impact factors on the province’s socioeconomic activities and assessment of the strength of cause–effect relationships in terms of magnitude and importance. Land use planning, surface water, and the length of the dry season are considered the most important causes, with the overall highest scores for both magnitude and importance in the cause–effect relationship. The largest effects of the different factors are perceived on water supply for agriculture and household use. Water availability and land use planning are important remedial action domains, while drought and land cover require monitoring to assess impacts. The indicators of cause and effect can be used in a longer-term general monitoring and assessment framework to ...

European agri-environment programmes are based on the common principle that farmers deliver environmental services for which society pays. Due to the voluntary nature of agri-environment measures (AEM), the issue of farmers' motives or reasons for participation has been an important topic of investigation in past years. The present paper examines farmers' rationale for participation in AEM against the backdrop of continued debate over whether to develop relatively simple measures that can be readily applied by many farmers or give greater priority to measures that are more targeted - i.e. to the specific management requirement of particular habitats or species - but are often more complex. The paper draws on empirical material from a case study in the Dyle valley, Belgium, including in-depth interviews, expert consultations and a mail survey. It was sought not only to identify and quantify the importance of separate reasons for participation, but also to reveal how these reasons and other elements of relevance were logically interrelated in the explanation that farmers themselves give for their participation. As a result, six modes or styles of participation were identified: opportunistic, calculative, compensatory, optimising, catalysing and engaged. The analyses suggest that there were notable differences in that both separate reasons for and modes of participation do vary with the complexity of the measures' requirements. Overall, the study demonstrates that participation in AEM is not simply a matter of weighing the money against the effort for adoption. Whereas money is an important driver for participation (in particular, for those adopting complex AEM) it plays widely differing roles depending on the level of farmers' reasoning (farm enterprise, single practice or landscape feature) and the importance they give to other considerations (environmental effect, production potential of land, goodness of fit, etc.). Practical implications are drawn for both policy makers and programme managers who develop and make available tailor-made support. © 2013 Elsevier Ltd.

Soil erosion forms a major threat to European soil resources. Although soil is a vital and largely non-renewable resource, it has not been the subject of comprehensive EU action so far. A thematic strategy for soil protection, which recognises soil erosion as one of the major threats, has currently been placed high on Europe’s political Agenda. Assessing and monitoring soil erosion is needed to evaluate the impact of, inter alia, agricultural and land use policies in Europe. The driving force–pressure–state–impact–response (DPSIR) policy framework, applied to soil erosion, is reviewed and suggestions for improvements are proposed. The agri-environmental indicators (AEIs) of soil erosion are discussed in relation to data availability, policy requirements and analytical soundness. We propose a reviewed framework and a set of soil erosion indicators that can be objectively calculated, validated against measurements or observations and evaluated by experts.

We present preliminary fluid dynamic simulation results of ethylene polymerization dense fluidized bed using the two-phase flow numerical code ESTET-ASTRID developed by Electricite de France for CFB boilers and based on the two-fluid modelling approach. The continuous phase consists of gas and the dispersed phase consists of catalyst particles. The particle fluctuating motion is modelled using two-separate transport equations, on the particle kinetic energy and the fluid-particle covariance, developed in the frame of kinetic theory of granular medium accounting for particle-particle and fluid-particle interactions. Time-dependent 2D and 3D simulations have been performed for industrial and pilot reactor operating conditions

A methodology was developed for an integrated assessment of land resources and land use, and applied to Ikem, south-eastern Nigeria. Findings from participatory rural appraisals (PRA) were related to two sets of aerial photographs (1962: 1:6000; 1982: 1:40,000). A two level PRA elicited relationships between soil-landscapes, land cover, land use and local classification schemes at both individual and village decision-making levels. At the field scale, local knowledge on the land was coupled with scientific data collected along toposequences and additional verification transects. Individually owned homegardens are agro-forestry systems involving field crops, vegetables and valued multi-purpose trees such as oil palm. The family-owned fields involve a mixture of food and tree crops. The land cover was a good indication of the fallow period used on fields in the communal farmlands as woody species no longer establish in short fallow periods. At the village scale, participatory land resources mapping was combined with aerial photograph interpretation to create soil-landscape and land cover/use maps that can be used for planning purposes at the local government. Additional archival research supported evidence that the growing population and subsequent land scarcity has led to shortened fallow periods and reduced numbers of woody species in the farmlands. The establishment of new settlements and the gradual increase of private land followed by the planting of tree cash crops have intensified agricultural land use resulting in a higher tree density across a larger area. Agricultural expansion predominantly took place on the relatively fertile land along the rivers. Results indicate the need for a non-ambiguous government policy concerning land tenure that recognises traditional land ownership dynamics.

An integrated survey along a continuum of two representative toposequences, crossing fluvial and interfluvial landscapes downstream of the confluence of two perennial rivers of the upper reaches of the River Ebonyi catchment resulted in a methodology for characterising toposequences and for identifying priorities for land evaluation. The so-called Integrated Toposequence Analysis (ITA) merges conventional biophysical surveying and participatory research techniques along toposequences and sets a framework for developing relational databases for land resource mapping at village and catchment scale. Relationships between physiographic position, soil characteristics, vegetation and land use demonstrate the physical and human influences affecting the current land status along the catenae. Indigenous appraisal of soil characteristics and productivity provides insight in current land use strategies at farm level, whereas, analysis from standard biophysical methods demonstrates the constraints to present land use trends. Results indicate the limited scope for further agricultural intensification on the upland interfluve areas with the present farming system practices, and show the increasing pressure to exploit the fluvial wetlands.

A method was developed for crop area mapping inspired by spectral matching techniques (SMTs) and based on phenological characteristics of different crop types applied using 100-m Proba-V NDVI data for the season 2014–2015. Ten-daily maximum value NDVI composites were created and smoothed in SPIRITS (spirits.jrc.ec.europa.eu). The study sites were globally spread agricultural areas located in Flanders (Belgium), Sria (Russia), Kyiv (Ukraine) and Sao Paulo (Brazil). For each pure pixel within the field, the NDVI profile of the crop type for its growing season was matched with the reference NDVI profile based on the training set extracted from the study site where the crop type originated. Three temporal windows were tested within the growing season: green-up to senescence, green-up to dormancy and minimum NDVI at the beginning of the growing season to minimum NDVI at the end of the growing season. Post classification rules were applied to the results to aggregate the crop type at the plot level. The overall accuracy (%) ranged between 65 and 86, and the kappa coefficient changed from 0.43–0.84 according to the site and the temporal window. In order of importance, the crop phenological development period, parcel size, shorter time window, number of ground-truth parcels and crop calendar similarity were the main reasons behind the differences between the results. The methodology described in this study demonstrated that 100-m Proba-V has the potential to be used in crop area mapping across different regions in the world.

We aimed to characterise the coincidence of yield variations with weather variables for major field crops using long-term datasets and reveal whether there are commonalities across the European agricultural regions. Long-term national and/or regional yield datasets were used from 14 European countries (total of 25 regions). Crops studied were spring and winter barley and wheat, winter oilseed rape, potato and sugar beet. Relative yield deviations were determined for all crops. Meteorological data on monthly means for temperature variables, solar radiation, accumulated precipitation and evapotranspiration were provided for the relevant agricultural regions of each country for 1975-2008. Harmful effects of high precipitation during grain-filling in grain and seed crops and at flowering in oilseed rape were recorded. In potato reduced precipitation at tuber formation was associated with yield penalties. Elevated temperatures had harmful effects for cereals and rapeseed yields. © 2010 Elsevier B.V. All rights reserved., JRC.H.4-Monitoring Agricultural Resources

Agricultural production is largely determined by weather conditions during the crop growing season. An important aspect of crop yield estimation concerns crop growth development. The occurrence of meteorological events such as frosts, droughts or heat stress during the crop life cycle or during certain phenological stages helps explain yield fluctuations of common arable crops. We developed a methodology and visualisation tool for risk assessment, and tested the workflow for drought and frost risk for winter wheat, winter barley and grain maize in Belgium. The methodology has the potential to be extended to other extreme weather events and their impacts on crop growth in different regions of the world. ispartof: Advances in Science and Research vol:18 pages:21-25 status: published

Attractive landscapes are diverse and resilient landscapes that provide a multitude of essential ecosystem services. The development of landscape policy to protect and improve landscape attractiveness, hereby ensuring the provision of ecosystem services, is ideally adapted to region specific landscape characteristics. In addition, trends in landscape attractiveness may be linked to certain policies, or the absence of policies over time. A spatial and temporal evaluation of landscape attractiveness is thus desirable for landscape policy development. In this paper, a landscape attractiveness monitoring framework based on geospatial data was developed for Flanders (Belgium) as a case study. Large local differences in landscape quality in (i) rural versus urban areas and (ii) between the seven agricultural regions in Flanders were found. This observed spatial variability of landscape attractiveness demonstrated that a localized approach, considering the geophysical characteristics of each individual region, would be required in the development of landscape policy to improve landscape quality in Flanders. Some trends in landscape attractiveness were related to agriculture in Flanders, e.g. a slight decrease in total agricultural area, decrease in dominance of grassland, maize and cereals, a decrease in crop diversity, sharp increase in adoption of Agri Environmental Agreements (AEA) and a decrease in bare soil conditions in winter. The observed trends and spatial variation in landscape attractiveness can be used as a tool to support policy analysis, assess the potential effects of future policy plans, identify policy gaps, and evaluate past landscape policy. ispartof: Land vol:10 issue:7 pages:703-703 status: Published online