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
Landslide Susceptibility Mapping for the Urmia Lake basin, Iran: A multiCriteria Evaluation Approach using GIS
Although typically small in terms of their spatial footprint, landslide hazards are relatively frequent in Northern Iran. We assess landslide susceptibility for the nearly 20.000 km2 large study area of the Urmia lake basin which is dominated by agricultural land use but includes the major settlements areas of the East Azerbaijan province, Iran. Landslide factors are established in form of GIS dataset layers including topography, geology, climatology and land use. After pre-processing all data layers are standardized based on a fuzzy logic model. An Analytical Hierarchical Process (AHP) delivers the weights for the GIS-analysis. Datasets are combined by GIS spatial analysis techniques and a landslide susceptibility map of the study area is created. An existing inventory of known landslides within the case study area was compared with the resulting susceptibility map. We found that high susceptible zones cover about 4.47% (944 km2) of the total area whereby geological outcrops of sedimentary and volcanic formations such as volcanic ash contribute most to the landslide susceptibility. Due to the dynamic growth of settlements especially in the vicinity of the city of Tabriz landslide hazards may cause even more damage in the future.The resulting information of this research is useful for a) a better understanding of existing landslides and their origins in North-Western Iran, b) supporting emergency decisions and c) prioritization of efforts for the reduction and mitigation of future landslide hazards.
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