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
The Ribeira Valley region (State of Sao Paulo, Brazil) hosts the largest Brazilian Atlantic forest reserve. The region was an important mineral district during the '60s, from where several tons of lead and other metals were exploited. Residual materials produced by the mining are diffused in the environment until today. The area also encompasses a regional arsenium anomaly associated with unexplored gold deposits. The population presently living in this region performs basic farming activities, from which most of their food is yielded. These features coupled together imply in a complex relationship between natural and anthropogenic factors that are likely to affect the life and health of the local communities. The aim of this paper is to apply digital data integration techniques for environmental risk assessment in the Ribeira Valley using environmental geochemistry. Geochemical, digital elevation and remote sensing data (Landsat Thematic Mapper) were merged and analyzed using a geographical information system. The assumed model considered environmental mobilization through erosion and anomalous As-Pb areas. Data were analyzed through Boolean and fuzzy logic techniques. Fuzzy logic proved superior in this case study as it allowed not only the detection but also the distinction between low, moderate and high environmental risk areas.
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