Land use and land cover (LULC) data is essential to environmental and ecological research. However, semantic
heterogeneous of land use and land cover classification are often resulted from different data resources, different cultural
contexts, and different utilities. Therefore, there is need to develop a method to measure, compare and integrate between
land cover categories. To understand the meaning and the use of terminology from different domains, the common
ontology approach is used to acquire information regarding the meaning of terms, and to compare two terms to
determine how they might be related. Ontology is a formal specification of a shared conceptualization of a domain of
interest. LULC classification system is a ontology. The semantic similarity method is used to compare to entities of three
LULC classification systems: CORINE (European Environmental Agency), Oregon State (USA), and Taiwan. The
semantic properties and relations firstly have been extracted from their definitions of LULC classification systems. Then
semantic properties and relations of categories in three LULC classification systems are mutually compared. The
visualization of semantic proximity is finally presented to explore the similarity or dissimilarity of data. This study
shows the semantic similarity method efficiently detect semantic distance in three LULC classification systems and find
out the semantic similar objects.
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