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
Transition times between phenological stages of a crop and the elapsed time of a phenological stage effects several parameters that are used in most of the yield evaluation methods. This study is about using the meteorological data and images from ground stations that are provided by TARBIL (Turkish Agricultural Monitoring and Information Systems) Project's to identify the transition dates between phenological stages of the specific crops. There are more than 300 working stations which are built next to agricultural fields in all over Turkey, and these stations have sensors that collect meteorological parameters that are reported in 10 minutes intervals from each site. Also the image data with different zoom rate is acquired in RGB format at 30 minutes period. In this study, an algorithm designed to observe the phenological course and detect the changes. Each stage has a different course than previous stage and the after one. 5 major stages are considered in this study to detect the transition dates. Two different process are applied and then their outcomes used for determining the transition dates of crops. Firstly, the daily images that are collected from TARBIL stations converted to HSV (Hue, Saturation, Value) color space then the green rate of these images are calculated. In a date base timeline, these calculated values create a green rate/date graph. To increase the correctness of the graph and decrease the noise level of the data, a noise filter is used on the dataset then the graph recreated. In the second step; GDD values are calculated from the meteorological data that collected from TARBIL stations. With respect to these GDD values, chosen crop's estimated phenological calendar is calculated. In the green rate/date graph there are refraction points that associates with a change in the phenological state. According to these refractions a new phenological calendar of the chosen crop is made.
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