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• Extrapolation_domain_analysis abstract "Extrapolation domain analysis (EDA) is a methodology for identifying geographical areas that seem suitable for adoption of innovative ecosystem management practices on the basis of sites exhibiting similarity in conditions such as climatic, land use and socio-economic indicators. Whilst it has been applied to water research projects in nine pilot basins, the concept is generic and can be applied to any project where accelerating change being considered as a central development objective. Many research for development programmes, need to ensure their research impact local areas, and that collectively contribute to spreading success to other areas, through the processes of ‘up or out scaling’.The outputs of the method thus far have been used to quantify the global economic impact of implementing particular innovations together with its effect on water resources (Bouman et al., 2007). The research has stimulated members of several of the Challenge Program for Water and Food projects to explore potential areas for scaling out. Such is the case of the Quesungual agroforestry system, which is moving towards new areas in parallel with areas identified by the EDA method.Extrapolation domain analysis (EDA) is a combined approach that incorporates a number of spatial analysis techniques. It was first investigated in 2006, when it was applied to assess how similarity analysis can be used to scale out research findings within seven Andes pilot systems of basins. The method developed further the research around the Homologue analysis by incorporating socio-economic variables in the search for similar sites around the Tropics. It has since been used to evaluate ‘Impact pathways’ and Global Impact Analysis.To derive the extrapolation domains, Bayesian and frequentist statistical modelling techniques are used. The weights-of-evidence (WofE) methodology is applied; this is based largely on the concepts of Bayesian probabilistic reasoning. In essence, statistical inference is based on determining the probability of target sites adopting the change demonstrated in pilot areas. The assumption is that a collection of training points will, in aggregate, have common characteristics that will allow their presence in other similar sites to be predicted. It is based on the collection of factors (used to create evidential theme data layers) that prove to be consistent with successful implementation at pilot sites and assumes that if target sites exhibit similar socio-economic, together with climatic and landscapes attributes to pilot sites, then there is strong evidence to suggest that out-scaling to these sites will succeed.To determine the similarity of climatic conditions across a geographical area to those exhibited by the pilot site, a technique developed by Jones et al. (2005) called ‘Homologue’ is used for identifying similar environments throughout the Tropics. The pixel resolution at which this is processed is 2.43 arc minutes, or 4.5 km at the equator.".
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• Extrapolation_domain_analysis wikiPageRevisionID "526594604".
• Extrapolation_domain_analysis wikiPageWikiLink Agroforestry.
• Extrapolation_domain_analysis wikiPageWikiLink Bayesian_probability.
• Extrapolation_domain_analysis wikiPageWikiLink Category:Bayesian_statistics.
• Extrapolation_domain_analysis wikiPageWikiLink Category:Ecosystems.
• Extrapolation_domain_analysis wikiPageWikiLink Ecosystem.
• Extrapolation_domain_analysis wikiPageWikiLink Impact_evaluation.
• Extrapolation_domain_analysis wikiPageWikiLink Land_use.
• Extrapolation_domain_analysis wikiPageWikiLink Methodology.
• Extrapolation_domain_analysis wikiPageWikiLink Participatory_Impact_Pathways_Analysis.
• Extrapolation_domain_analysis wikiPageWikiLink Participatory_impact_pathways_analysis.
• Extrapolation_domain_analysis wikiPageWikiLink Spatial_analysis.
• Extrapolation_domain_analysis wikiPageWikiLink Water_resources.
• Extrapolation_domain_analysis wikiPageWikiLinkText "Extrapolation domain analysis".
• Extrapolation_domain_analysis hasPhotoCollection Extrapolation_domain_analysis.
• Extrapolation_domain_analysis wikiPageUsesTemplate Template:Clarify.
• Extrapolation_domain_analysis wikiPageUsesTemplate Template:Refimprove.
• Extrapolation_domain_analysis subject Category:Bayesian_statistics.
• Extrapolation_domain_analysis subject Category:Ecosystems.
• Extrapolation_domain_analysis hypernym Methodology.
• Extrapolation_domain_analysis type Article.
• Extrapolation_domain_analysis type Software.
• Extrapolation_domain_analysis type Article.
• Extrapolation_domain_analysis comment "Extrapolation domain analysis (EDA) is a methodology for identifying geographical areas that seem suitable for adoption of innovative ecosystem management practices on the basis of sites exhibiting similarity in conditions such as climatic, land use and socio-economic indicators. Whilst it has been applied to water research projects in nine pilot basins, the concept is generic and can be applied to any project where accelerating change being considered as a central development objective.".
• Extrapolation_domain_analysis label "Extrapolation domain analysis".
• Extrapolation_domain_analysis sameAs Extrapolace_analýzy_domén.
• Extrapolation_domain_analysis sameAs m.05sz24q.
• Extrapolation_domain_analysis sameAs Q5422245.
• Extrapolation_domain_analysis sameAs Q5422245.
• Extrapolation_domain_analysis wasDerivedFrom Extrapolation_domain_analysis?oldid=526594604.
• Extrapolation_domain_analysis isPrimaryTopicOf Extrapolation_domain_analysis.