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
In this paper we propose to identify the number of urban categories that can be retrieved from very high resolution TerraSAR-X data. For this task a semi-automated procedure was built in order to search in large Earth Observation database for similar sub-images (i.e. patches) and group them in the same semantic category. The dataset consists of 39 scenes over the world: 18 scenes in Asia, 15 scenes in Europe, 5 scenes in North and South America, and 1 scene in Africa. These scenes are grouped in three different types of collections (a total of 16 collections are generated) and the semantic categories in each collection are retrieved. A total of 320 categories are identified and those that contain man-made structures in the urban area are kept and the rest of categories (e.g., agriculture, water, etc.) are discarded. These categories represent between 50% and 65% from the total number of retrieved categories in each collection.
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