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.

You can access and play with the graphs:

Discover all records
Home page


Spatial dynamics for relative contribution of cropping pattern analysis on environment by integrating remote sensing and GIS


Agriculture resources reflected to be one of the most imperative renewable and dynamic natural resources. Agricultural sustainability has the premier priority in all countries, whether developed or developing. Cropping system analysis is indispensable for grinding the sustainability of agricultural science. Crop alternation is stated as growing one crop after another on the same piece of land in altered timings (seasons) without prejudicing the soil fertility. The study has been conducted for Fatehabad district of Haryana State of Indo-Gangetic plains in India. This paper generated cropping pattern and crop rotation maps of Fatehabad district. Multi-date IRS LISS-III digital data of different cropping seasons of 2007-08 have been used for this study. The present study relies on data from remote sensing combined with ground observations. Multi-date images of Rabi season images were geo-referenced using master images. Multi-date images of Kharif and single date image of summer seasons were geo-referenced with geo-referenced Rabi season image using image-to-image registrations and nearest neighborhood resampling method was applied. Multilayer stack were prepared for Kharif and Rabi cropping seasons. Stacked images of different seasons were classified using complete enumeration approach and unsupervised ISO-Data clustering classifier with district outside and non-agriculture mask based on some defined conditions

  • IN
  • Banasthali_Univ (IN)
  • Kumaun_Univ (IN)
Data keywords
  • digital data
Agriculture keywords
  • agriculture
  • crop system
Data topic
  • information systems
  • sensors
Document type

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

Institutions 10 co-publis
    Powered by Lodex 8.20.3
    logo commission europeenne
    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.