GeoS 2005: GeoSpatial Semantics pp 107-119 | Cite as
Using Semantic Similarity Metrics to Uncover Category and Land Cover Change
Conference paper
Abstract
Analysis of geographic data that uses a nominal measurement framework is problematic since it limits the possible analytic methods that can be applied. Land cover change analysis is an example of this where both the actual change analysis as well as classification changes over time can be problematic. This study illustrates the use of semantic similarity metrics on parameterized category definitions, and how these metrics can be used to assess land cover change over time as a degree of perceived change with respect to the original landscape state. It also illustrates how changes of the categories, the classification system, over time can be analyzed using semantic similarity measures.
Keywords
Land Cover Land Cover Change Semantic Similarity Impervious Surface Land Cover Class
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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