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

CO-POLAR SAR DATA CLASSIFICATION AS A TOOL FOR REAL TIME PADDY-RICE MONITORING

en
Abstract

The crop phenology retrieval on precision agriculture has been an important research area with the increasing demand on crops. Remotely sensed Synthetic Aperture Radar (SAR) data provides a simple possibility for automatic monitoring of agricultural fields due to the its inherit all-weather monitoring capability. Most of the studies rely on morphology based modelling of the electromagnetic backscattering which requires Monte Carlo simulations. In this paper, instead of modelling the backscattering of the signals for monitoring the crop fields, a classification scheme was implemented on the data acquired by TerraSAR-X by using the features extracted from backscattering coefficients with the machine learning algorithms which are Support Vector Machines, k-Nearest Neighbor and Regression Tree.

en
Year
2015
en
Country
  • TR
Organization
  • Istanbul_Tech_Univ_ITU (TR)
Data keywords
  • machine learning
en
Agriculture keywords
  • agriculture
en
Data topic
  • big data
  • modeling
  • sensors
en
SO
2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Istanbul_Tech_Univ_ITU (TR)
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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.