Land-cover harmonisation and semantic similarity: Some methodological issues

Abstract

Harmonisation of land-cover data relates to spatial data integration and therefore needs to consider the data concepts adopted and the spatial, temporal, semantic and quality aspects of the data. Differences in semantic concepts are often considered the key obstacle to data integration and interoperability. If the problem of harmonisation is limited to the variation in the semantic content of data expressed as differences in categorisation, then various approaches have been developed to address the methodological issues and for computing semantic similarity. Five Nordic class sets were selected for establishing correspondences between their semantic class contents using the parameterised land cover classification system (LCCS) as a reference system. Subsequently, semantic similarities between pair-wise classes were calculated using a module of LCCS. This article first examines the aspects of land-cover harmonisation and the LCCS methodologies for categorisation and semantic similarity. It then discusses the functioning of LCCS as a reference system in which the more or less corresponding class of the original Nordic classes was determined and the semantic similarity indices computed. Suggestions are provided for improvements in the LCCS methodology, both in establishing correspondences and for computing semantic similarity. Recommendations are given for the way forward in land-cover harmonisation and for measures to express the quality of harmonisation of the semantic contents of class sets at class set level and individual class level.