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
Managing salinity in irrigated agriculture is crucial for minimising its negative environmental impacts and for ensuring the long-term sustainability of irrigated agriculture. It demands establishing rapid monitoring systems that help develop sustainable management plans. Remote sensing offers several advantages over the conventional proximal methods to map and predict areas at salinity risk. This paper presents an integrated approach to characterize soil salinity using remotely-sensed data in the District Faisalabad, Punjab, Pakistan. The IRS-1B LISS-II digital data was acquired and analysed in combination with field data and topographical maps. Remotely-sensed data based salinity indices or band combinations were developed to monitor the occurrence pattern of salt-affected soils. Using supervised maximum likelihood classification, the images were classified into eight land use classes with an overall accuracy of around 90%. The classified images showed that 22.2% of the total area was under salt-affected soils in 1992. The occurrence pattern of salt-affected soils varied with positive and negative trends during 1992-1995 to a minimum of 10.6%. The delineation analysis into levels of saline soils revealed three types based on USDA classification (USDA, 1954). The slightly saline, moderately saline and strongly saline soils during 1992 were in the order of 15%, 3%, and 1% respectively. The interactive behaviour of salinity and sodicity and their combinations showed that saline-sodic soils occurred predominantly ranging from 6.9% to 17.3% of the salt-affected soils. The shallow watertable was found to be of hazardous quality in 28% of the study area. The relationship between salt-affected soils, waterlogged soils and groundwater quality revealed that 60-70% of the salt-affected soils occurred in shallow watertable areas during 1992-1995. The reuse of poor quality groundwater for irrigation and the failure of tile drainage system in the area are likely to further increase the risk of salinisation in the Indus Basin of Pakistan. (C) 2010 Elsevier Ltd. All rights reserved.
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