Semantic integration of geospatial concepts - a study on land use land cover classification systems

Title of Document: SEMANTIC INTEGRATION OF GEOSPATIAL CONCEPTS – A STUDY OF LAND USE LAND COVER CLASSIFICATION SYSTEMS Hua Wei, Ph. D., 2011 Directed By: Professor John R. G. Townshend Department of Geography University of Maryland, College Park In GI Science, one of the most important interoperability issues relates to land use and land cover (LULC) data, because it is a key to the evaluation of LULC’s many environmental impacts throughout the globe (Foley et al. 2005). Accordingly, this research aims to address the interoperability of LULC information derived by different authorities using different classificatory approaches. LULC data are described by LULC classification systems. The interoperability of LULC data hinges on the semantic integration of LULC classification systems. Existing works on semantically integrating LULC classification systems has a major drawback in finding comparable semantic representations from textual descriptions. To tackle this problem, we borrowed the method of comparing documents in information retrieval, and applied it to comparing LULC category names and descriptions. The results showed notable improvement compared to previous work. However, lexical semantic methods are not able fully to solve the semantic heterogeneities in LULC classification systems: the confounding conflict – LULC categories under similar labels and descriptions have different LULC status in reality, resulting in a naming conflict – LULC categories under different labels can represent similar LULC type. Without confirmation of their actual land cover status from remote sensing, lexical semantic method cannot achieve reliable matching. To discover confounding conflicts and reconcile naming conflicts, we developed an innovative method by applying remote sensing to the integration of LULC classification systems. Remote sensing is a means of observation of actual LULC status of individual parcels. We calculated parcel level statistics from spectral and textural data, and used these statistics to calculate category similarity. The matching results showed this approach fulfilled its goal of overcoming semantic heterogeneities and achieved more reliable and accurate matching between LULC classifications in the majority of cases. To overcome the limitations of both methods, we combined the two by aggregating their output similarities, and achieved better integration. LULC categories that display noticeable differences between lexical semantics and remote sensing once again remind us of semantic heterogeneities in LULC classification systems that must be overcome before LULC data from different sources become fully interoperable. SEMANTIC INTEGRATION OF GEOSPATIAL CONCEPTS – A STUDY OF LAND USE LAND COVER CLASSIFICATION SYSTEMS