The separation of land cover from land use with data primitives.

The common confusion of land cover and land use in many datasets is problematic for many data integration activities. This paper proposes an approach for the separation of land cover and land use based on data primitives. Data primitives are those dimensions that describe at the most fundamental level the processes under investigation. In this case they provide building blocks that to allow land cover and land use to be separated. A series of data primitives were identified from the literature and applied to US National Land Cover Dataset (2001). Mapped outputs, separating the concepts of form (land cover) and function (land use), show the degree of land use, the degree of land cover and locations where the concepts of use and cover are confused. The separation of land cover and land use facilities the integration of land data for environmental modelling and planning activities. The work promotes the need for land use and land cover to be maintained as distinct concepts in data collection activities.