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
The use of the theory of fussy logic in satellite image classification of mix cover: An urban case in Merida, Venezuela
The Theory of Fuzzy Logic is a technique with applications in different fields. It describes properties with a continuous variation in their values, associating parts from these values to a semantic label. For example, the change when passing from a dense forest to a disperse forest is not an immediate one, a transition area exists that cannot be classified neither with one nor the other label and shows characteristics of both forest types. In this case the Fuzzy Logic theory is useful to assign percentages of coverage for either type of forest. The same occurs in agricultural and urban areas. When making supervised classification of satellite images to generate use and cover maps, this type of problems arises in urban and agricultural areas, and in ecotones. The supervised classification has been made traditionally with "hard" classifiers, which only allow to "train" the system in such a way that a given use or cover is exclusive of others. The use of the Theory of Fuzzy Logic has been proposed to cope with the existence of transition areas or mixed uses in the terrestrial surface. In the present work two supervised classification types are developed for satellite images in an urban area, in Merida, Venezuela and its surroundings: i) the traditional form of "hard classification", and ii) using fuzzy logic, "soft classification". Two "resulting images" different in aspect are obtained, being the one derived from the second approach a better representation of the terrestrial surface.
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