The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
We present a pan-European irrigation map based on regional European statistics, a European land use map and a global irrigation map. The map provides spatial information on the distribution of irrigated areas per crop type which allows determining irrigated area,. at the level of spatial modelling units. The map is a requirement for a European scale assessment of the impacts of irrigated agriculture on water resources based on spatially distributed modelling of crop growth and water balance. The irrigation map was compiled in a two step procedure. First, irrigated areas were distributed to potentially irrigated crops at a regional level (European statistical regions NUTS3), combining Farm Structure Survey (FSS) data on irrigated area, crop-specific irrigated area for crops whenever available, and total crop area. Second, crop-specific irrigated area was distributed within each statistical region based on the crop distribution given in our land use map. A global map of irrigated areas with a 5' resolution was used to further constrain the distribution within each NUTS3 based on the density of irrigated areas. The constrained distribution of irrigated areas as taken from statistics to a high resolution dataset enables us to estimate irrigated areas for various spatial entities, including administrative, natural and artificial units, providing a reasonable input scenario for large-scale distributed modelling applications. The dataset bridges a lap between global datasets and detailed regional data on the distribution of irrigated areas and provides information for various assessments and modelling applications. (C) 2008 Elsevier B.V. All rights reserved.
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