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Assessing the Geographic Representativity of Farm Accountancy Data
Rural Economy and Development Programme, Teagasc, Athenry, Co. Galway, Ireland
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Received: 6 December 2012; in revised form: 25 January 2013 / Accepted: 28 January 2013 / Published: 6 February 2013
Abstract: The 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.
Keywords: FADN; agri-environment; address matching; agriculture
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Cite This Article
MDPI and ACS Style
Green, S.; O'Donoghue, C. Assessing the Geographic Representativity of Farm Accountancy Data. ISPRS Int. J. Geo-Inf. 2013, 2, 50-66.
Green S, O'Donoghue C. Assessing the Geographic Representativity of Farm Accountancy Data. ISPRS International Journal of Geo-Information. 2013; 2(1):50-66.
Green, Stuart; O'Donoghue, Cathal. 2013. "Assessing the Geographic Representativity of Farm Accountancy Data." ISPRS Int. J. Geo-Inf. 2, no. 1: 50-66.