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
Object-based detection of LUCC with special regard to agricultural abandonment on Tenerife (Canary Islands)
The island Tenerife has always been used for intensive agriculture, whereby the natural landscape was continuously altered. Especially mountainous areas with suitable climate conditions have been drastically transformed for agricultural use by building of large terraces to get flat surfaces. In recent decades political and economic developments lead to a transformation process (especially inducted by an expansive tourism), which caused concentration- and intensification-tendencies of agricultural land use as well as agricultural set-aside and rural exodus. In order to get information about the land use and land cover (LULC) patterns and especially the agricultural dynamics on Tenerife, a multi-scale, knowledge-based classification procedure for recent RapidEye data was developed. Furthermore, a second detection technique was generated, which allows an exact identification of the total ever utilised agricultural area on Tenerife, also containing older agricultural fallow land or agricultural set-aside with a higher level of natural succession (under the assumption that long-term fallow areas can be detected mainly together with old agricultural terraces and its specific linear texture). These areas can hardly be acquired in the used satellite imagery. The method consists of an automatic texture-oriented detection and area-wide extraction of linear agricultural structures (plough furrows and field boundaries of arable land, utilised and non-utilised agricultural terraces) in current orthophotos of Tenerife. Through the detection of recent agricultural land use in the satellite imagery and total ever utilised agricultural area in the orthophotos, it is possible to define the total non-active agricultural land as well as hot spots of agricultural decrease.
Inappropriate format for Document type, expected simple value but got array, please use list format