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
This article aims to be a contribution to the improvement of agricultural and environmental official statistics. Methods are applied to integrate information from state agency registers regarding crop area with ground data observed in random area samples. To improve the precision of crop area estimates in small areas (municipalities), methods using ground survey and remote sensing are applied. To improve temporal resolution of crop area estimators, methods based on time series analysis are applied. Agro-meteorological models are applied to improve crop yields statistics. A method is shown whereby crop rotation models may be a useful tool to forecast changes in the dynamics of the use of natural resources (soil, water and air) by agriculture and to foresee their environmental impact. Finally, a method to update and disaggregate information from territorial censuses on land uses is applied. These methods and models are illustrated in the framework of an information system belonging to the Spanish Ministry of the Environment and Rural and Marine Affairs. The relative improvement offered by each method is assessed by evaluating the precision gain of the proposed crop area estimates versus those currently used by the aforementioned information system.
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