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
An integrated Agricultural Land Quality Monitoring Information System based on Standard Plots and WebGIS
Agricultural land quality monitoring is a fundamental and key work for national food security and cultivated land protection that ensures the sustainable development of agriculture. Traditional land surveys usually take long term and huge effort to conduct, while RS technologies are mainly used to monitor the quantity change of land resources. The changing information of the Natural Quality Index (NQI), which directly reflects the agricultural land quality change, is still hard to assess and monitor. This paper takes Hubei Province as study area, where the newly deployed agricultural land standard plots play as key role in establishing an NQI modification model, making the original NQI from different second-class districts comparable with each other to a certain extent. The monitoring results are validated to match the actual distribution of agricultural land quality in Hubei Province, with two years' data collected from standard plots in 2009 and 2011 showing the agricultural land quality change in 14 counties. Finally, using ASP. NET, ArcGIS Server and database technologies, a Web GIS-based agricultural land quality monitoring information system is designed for the visualization, analysis and management on agricultural land quality monitoring information.
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