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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A framework for the geometric accuracy assessment of classified objects


European initiatives for data harmonization and the establishment of remote-sensing-based services aim at the production of up-to-date land-cover information according to generally valid standards for the accurate qualification of thematic classification results. This is particularly true since new satellite systems provide data of high temporal and geometric resolution. While methods for point-related thematic accuracy assessment have already been established for years, there is a need for a commonly accepted framework for the geometric quality of tematic maps. In this study, an open and extendable framework for the geometric accuracy assessment is presented. The workflow begins with the definition of basic geometric accuracy metrics, which are based on differences in area and position between samples of classified and reference objects. The combination of user-defined metrics enables both a geometric assessment of single objects as well as the total data set. In an example of thematically classified agricultural fields in a German test site, we finally show how object relations between classified and reference objects can be identified and how they affect the global accuracy assessment of the total data set.

  • DE
  • UG
  • Univ_Halle_Wittenberg (DE)
Data keywords
  • data harmonization
Agriculture keywords
  • agriculture
Data topic
  • information systems
  • modeling
  • 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.