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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Assessing land cover change in Kenya's Mau Forest region using remotely sensed data


Kenya's Rift Valley has been undergoing rapid land cover change for the past two decades, which has resulted in ecological and hydrological changes. An effort is under way to quantify the timing and rate of these changes in and around the River Njoro watershed located near the towns of Njoro and Nakuru using remote sensing and geographic information system (GIS) methods. Three Landsat TM images, representing a 17-year period from 1986 to 2003 in which the area underwent a significant land cover transition, were classified and compared with one another. Vegetation diversity and temporal variability, common to tropical and sub-tropical areas, posed several challenges in disaggregating classified data into sub-classes. An iterative approach for the resolving challenges is presented that incorporates unsupervised and supervised classification routines in coordination with knowledge-based spatial analyses. Changes are analysed at three spatial scales ranging from the highly impacted and deforested uplands to the watershed and landscape scales. Land cover transitions primarily occurred after 1995, and included large forest losses coupled with increases in mixed small-scale agriculture and managed pastures and degraded areas. These changes in cover type are highly spatially variable and are theorized to have significant impacts on ecological and hydrologic systems with implications for environmental sustainability.

  • US
  • KE
  • Univ_Wyoming (US)
Data keywords
  • knowledge
  • information system
  • knowledge based
Agriculture keywords
  • agriculture
Data topic
  • 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.