Abstract
AbstractAgricultural Census data is summarised over spatially coarse reporting units for reasons of farm confidentiality. This is problematic for research at a local level. This article describes an approach combining dasymetric and volume preserving techniques to create a national land use dataset at 1 km2 resolution. The results for an English county are compared with contemporaneous aggregated habitat data. The results show that the accurate estimates of local agricultural land use (Arable and Grass) patterns can be estimated when individual 1 km squares are combined into blocks of > 9 squares, thereby providing local estimates of agricultural land use. This in turn allows more detailed modelling of land uses related to specific livestock and cropping activities. The dataset created by this work has been subject to extensive external validation through its incorporation into a number of other national models: nitrate leaching (e.g. MAGPIE, NEAP‐N), waste, and pathogen modelling related to agricultural activity.
Highlights
In this paper we demonstrate a method for generating local land use estimates at 1km2 from aggregated agricultural census data for England and Wales
A national dataset of land use was created at 1km2 for England and Wales based on aggregated June Agricultural Census (JAC) data for 2000, reported at higher geographies
The results of this work found a good correspondence between the monthly profiles of predicted concentrations of faecal coliforms at the tidal limit in two selected study areas and the actual contamination found in shellfish. The results of this analysis show that land use data reported at coarse levels of geographic detail for reasons of confidentiality can be reliably disaggregated into finer detailed target zones if the interpolation is appropriately constrained. In this case non-agricultural land use information from a number of sources was iteratively added into the solution, constrained by the other data on the actual amount of agricultural land use
Summary
In this paper we demonstrate a method for generating local land use estimates at 1km from aggregated agricultural census data for England and Wales. The June Agricultural Census (JAC) summarises land use over reporting units that are spatially coarser than the level at which the data was originally collected for reasons of confidentiality or expediency. Information on individual agricultural holdings is confidential and only aggregate data are released in the form of Parish, County, and latterly NUTS summaries. There are significant and acknowledged problems in summary agricultural census data, especially related to the nature of the statistical reporting units (Coppock 1955, 1960). Farms may not sit precisely in those parishes only their ‘headquarters’, usually location of the farmhouse This results in both under- and over-estimation when the data for those units are analysed. The recent focus of much agricultural research has been on the role of the farm as a point of production within a wider, global food system (e.g. Whatmore, 1995; Sullivan et al, 2004); on the nature of farm diversification activities (e.g.; Evans and Ilbery, 1993; Leff et al, 2004) and the increased interest in agri-environmental issues (e.g. Cook and Norman, 1996; Chamberlain et al, 2000; Vaughan et al, 2003)
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