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Mary Brown [12-2011]:

Georeferencing Agricultural Survey Statistics

Diese Arbeit ist online verfügbar: Download


Georeferencing Agricultural Survey Statistics Annual agricultural statistical surveys gather a vast amount of information relating to agricultural practice which could potentially be of interest in other fields of study. This thesis explores ways of exploiting the spatial potential inherent within this numerical data. Numerical agricultural survey data are successfully georeferenced, providing spatial access to a decade of data for Canton Berne for the first time. After detailed examination of the survey content and of the associated Gelan agrarian information system's database, relevant data was identified and a method was developed to georeference farmed land based on linking the numerical land parcels to cadastral geodata. The perimeter of farmed land was then reduced by subtracting ineligible land-use categories. The remaining perimeter was used as a base to georeference crop and livestock data per farm. These data not only give an indication of the agricultural intensity in any given region – e.g. by mapping livestock units per area of fertilized land – but also help to some extent to illustrate the levels of diversity in crop cover. These factors are significant in evaluating the potential for suitable habitat for farmland bird species. Less intensive farming methods have been proven to benefit species diversity and population numbers. Georeferenced output is successfully adapted and illustrated at varying scales, thereby revealing distinctive regional patterns and providing a new detailed indicator of agricultural intensity. The new spatial data produced in this study was developed with the particular interests of the Swiss Ornithological Institute in mind. The georeferenced agricultural survey statistics can provide them with significant new inputs relevant for population studies and analysis of habitat potential related to aspects of agricultural intensity. Although the methods developed in this study for georeferencing agricultural survey statistics are based on the situation in Canton Berne, they also provide scope for a general approach using the data collected by the government at a national level. Keywords: GIS, georeferencing, agricultural survey statistics, agricultural intensity, farmland birds, farmland habitat, livestock density, crop diversity.


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