e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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Geospatial analysis for utilizing the marginal land in regional biofuel industry: A case study in Guangdong Province, China


Due to the intensive and exhaustive land use in China, the so-called marginal land is expected to play a major role in supporting the biofuel industry of the country. We developed a regional-level framework of using geospatial information technologies to achieve an optimal utilization of the marginal land for biofuel production. The framework includes identifying marginal lands, evaluating optimality of the land for growing certain bioenergy crops, estimating local potential feedstock production, and finally selecting optimal sites for biofuel factories. We present a case study of farming Jatropha (Jatropha curcas L.) and Cassava (Manihot esculenta Crantz) in Guangdong, China. The marginal land was identified from satellite imageries at a 30-m resolution. The optimality for growing the two species was evaluated using the Ecological Niche Models (ENMs), which incorporates local temperature, precipitation, soil, and terrain. The optimality value was then converted into potential feedstock production using a conversion model. The site selection for the factories incorporated the local potential feedstock production, the transportation cost measured by road distance, and the farming cost related to the land patch geometry. Each candidate site received an overall optimality score derived based on those factors. We identified five sites that have high scores and also minimal or none spatial overlaps of their supporting areas. Three of them (Zhanjiang, Yunfu, and Jieyang) are for Cassava, located on in southern Guangdong. Two (Qingyuan and Meizhou) are for Jatropha in northern Guangdong. (C) 2015 Elsevier Ltd. All rights reserved.

  • CN
  • US
  • Guangzhou_Univ (CN)
  • Dartmouth_Coll (US)
Data keywords
  • information technology
Agriculture keywords
  • farming
Data topic
  • information systems
  • sensors
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
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    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.