Research making use of satellite data for land change science has developed in the last decades. However, analysis of land use has not developed with the same speed as development of new satellite sensors and available land cover data. Improvement of land use analysis is possible, but more advanced methods are needed which make it possible to link image data to analysis of land use functions. To make this linking possible, variable which affect farmer's long term decisions must be taken into account in analysis as well as the relative importance of the landscape itself. A GIS-based tool for the measurement of local spatial context in satellite data is presented in this paper and used to explore the relationship between land covers present in satellite data and land use represented in official databases. By the use of the developed tool, a land configuration image (LCI) over the Siljan area in northern Sweden was produced and used for analysis. The results are twofold. First, the produced LCI holds new information about variables that are relevant for the interpretation of land use. Second, the comparison with statistics of agricultural production shows that production in the study area varies depending on the relative land configuration. Villages consisting of relatively large-scale arable fields and less diverse landscape are less diverse in production than villages which consist of smaller-scale and more heterogonous landscapes. The result is especially relevant for land use studies and policymakers working on environmental and agricultural policies. We conclude that local spatial context is an endogenous variable in the relation between landscape configuration and agricultural land use.