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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Title

The use of the theory of fussy logic in satellite image classification of mix cover: An urban case in Merida, Venezuela

en
Abstract

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.

en
Year
2005
en
Country
  • VE
  • FR
Organization
  • Univ_Grenoble_Alpes (FR)
  • Grenoble_INP (FR)
Data keywords
  • semantic
en
Agriculture keywords
  • agriculture
en
Data topic
  • modeling
en
SO
INTERCIENCIA
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.