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
An Integrated Study of Geospatial Information Technologies for Surface Runoff Estimation in an Agricultural Watershed, India
Runoff is one of the important hydrologic variables used in most of the water resources applications. The Soil Conservation Service-Curve Number (SCS-CN) method is adopted for the estimation of surface runoff in the Mehadrigedda watershed area, Visakhapatnam district, India using multispectral remote sensing data, curve number approach and normal rainfall data. The main source of water in the Mehadrigedda watershed area is by rain, most of it drains off and only a little percolates into ground. The weighted curve number is determined based on antecedent moisture condition (AMC)-II with an integration of hydrologic soil groups (HSGs) and land use/land cover LULC categories. An integrated approach is applied to delineate the land use/land cover information as adopted from NRSA classification. The recording of daily rainfall data during the years 1997-2006 is collected from Indian Meteorological Department (IMD) rainguage center at Kottavalasa. It is observed that the annual rainfall-runoff relationship during 1997-2006, which is indicating that the overall increase in runoff with the rainfall of the watershed area. Integration of remote sensing (RS) and geographical infomation system (GIS) techniques provide reliable, accurate and up-to-date information on land and water resources.
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