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
Remote sensing data combined with crop model is an important application and development trend of current agricultural information technology, it can solve the problem that remote sensing or crop model cannot solve alone. In order to simulate crop growth and yield prediction in large scale, this paper using field test data to calibrate and validation the model parameters before apply to the winter wheat WOFOST model, than according to the actual environment of Xinxiang, simulate the growth in 3 different condition in the 2002-2003 growing season. Contrast the simulation value WOFOST model, using the Landsat-7 ETM retrieving leaf area index, define winter wheat's growth condition in each pixel, the remote sensing information combined with crop model is accomplished at pixel scale. Based on the actual production of Xinxiang winter wheat in 2003, compare the simulate results with the corresponding parameter, results shows that the method of this study method is feasible.
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