Semantically based reclassification of Danish land-use and land-cover information

Abstract

In recent years, the availability of georeferenced data has increased substantially, as have the number of producers and users of this information. As a consequence, there is a growing need for harmonization of data, not least in its classification descriptions. Unfortunately, inadequate metadata hampers understanding of how data sets are produced and what data classes represent. This study describes how five different categorical geodata sets for Denmark, ranging from habitat registrations through maps of agricultural land use to national topographic data, are integrated and how the integrated data set is reclassified to land-use and land-cover classes. All five data sets differ with respect to data acquisition, and description and classification methodologies, and none of the data distinguish between land use and land cover. The purpose of the reclassification was to produce maps of land use and land cover, with classes being compatible with the land cover classification system (LCCS) from the Food and Agriculture Organization of the United Nations. We identified land-cover and land-use classes from the LCCS that matched Danish conditions and cross-tabulated those classes with classes from the integrated Danish data set. Based on the semantic meaning of the class names from the integrated data set, we used heuristic associational knowledge to estimate their membership in the land-use and land-cover classes. The results are three land-use maps and five land-cover maps, indicating qualitative estimates of the presence of land-cover classes measured on an ordinal scale.