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dc.contributor.authorgreen, stuart*
dc.contributor.authorO'Donoghue, Cathal*
dc.date.accessioned2013-02-27T17:29:55Z
dc.date.available2013-02-27T17:29:55Z
dc.date.issued06/02/2013
dc.identifier.citationGreen S, O'Donoghue C. Assessing the Geographic Representativity of Farm Accountancy Data. ISPRS International Journal of Geo-Information. 2013; 2(1):50-66.en_GB
dc.identifier.issn2220-9964
dc.identifier.urihttp://hdl.handle.net/11019/334
dc.descriptionpeer-reviewed
dc.description.abstractThe environment affects agriculture, via soils, weather, etc. and agriculture affects the environment locally at farm level and via its impact on climate change. Locating agriculture within its spatial environment is thus important for farmers and policy makers. Within the EU countries collect detailed farm data to understand the technical and financial performance of farms; the Farm Accountancy Data Network. However, knowledge of the spatial-environmental context of these farms is reported at gross scale. In this paper, Irish farm accounting data is geo-referenced using address matching to a national address database. An analysis of the geographic distribution of the survey farms, illustrated through a novel 2D ranked pair plot of the coordinates, compared to the national distribution of farms shows a trend in the location of survey farms that leads to a statistical difference in the climatic variables associated with the farm. The farms in the survey have significantly higher accumulated solar radiation values than the national average. As a result, the survey may not be representative spatially of the pattern of environment x farm system. This could have important considerations when using FADN data in modelling climate change impacts on agri-economic performance.en_GB
dc.language.isoenen_GB
dc.publisherMDPI AG., Basel, Switzerlanden_GB
dc.relation.ispartofseriesISPRS International Journal of Geoinformation;vol 2
dc.subjectFADNen_GB
dc.subjectAgri-environmenten_GB
dc.subjectAddress matchingen_GB
dc.subjectAgricultureen_GB
dc.titleAssessing the Geographic Representativity of Farm Accountancy Dataen_GB
dc.typeArticleen_GB
dc.identifier.rmis6035
dc.identifier.doihttp://dx.doi.org/10.3390/ijgi2010050
refterms.dateFOA2018-01-12T07:59:03Z


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