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
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.
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