Spatial statistics allows to assess geographic distribution of phenomena – its concentration, magnitude and orientation of dispersion as well regularity or trends in occurrence within a space. The paper presents adaptation of point-based methods to measure spatial distribution of areal phenomena that concern agriculture: area of agricultural land, area of fertile agricultural land and soil pH. The source data in a form of chorochromatic maps (e.g. a vector soil map) are processed to 1 x 1 km grid data with use of the algorithm created in Model Builder. The research area – Lower Silesia – characterizes various environmental conditions that results in changeability of agricultural land productivity. Spatial statistics performed for a whole region would bring only global information on spatial distribution. Hence the Authors propose to conduct analysis within subareas that depict local changeability of studied phenomena. As the research is conducted in agricultural context, the subareas of similar agricultural land areas are created regarding the administrative units. Spatial distribution is described by: mean centre, standard distance and standard deviational ellipse. All three measures are weighted by a variable (i.e. the intensity of the phenomenon) as spatial distribution is not only about location, but the value of the phenomenon in particular location is important. Measures of spatial distribution drawn on a map yields clear and usually easy to interpret information on spatial character of a phenomenon. In some cases it may be useful to present these qualitative characteristics complemented with another type of cartographic visualization (e.g. a choropleth map. This paper presents maps about the application of spatial distribution measures into assessment of agricultural land productivity in the research.
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