Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Parameter estimation and hypothesis testing in linear models
Parameter estimation and hypothesis testing in linear models
Towards a theory of spatial database queries (extended abstract)
PODS '94 Proceedings of the thirteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Constraint query languages (preliminary report)
PODS '90 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A boundary-sensitive approach to qualitative location
Annals of Mathematics and Artificial Intelligence
Imprecision in Finite Resolution Spatial Data
Geoinformatica
Identification of Fuzzy Objects from Field Obseravtion Data
COSIT '97 Proceedings of the International Conference on Spatial Information Theory: A Theoretical Basis for GIS
The Algebraic Structure of Sets of Regions
COSIT '97 Proceedings of the International Conference on Spatial Information Theory: A Theoretical Basis for GIS
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
GIScience '02 Proceedings of the Second International Conference on Geographic Information Science
Linking image structures with medical ontology information
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Data semantics in location-based services
Journal on Data Semantics III
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Object reconstruction from remote sensed images is an actual research topic in computer vision, photogrammetry, and spatial information science. One of the most interesting related questions is the modeling of the uncertainty of knowledge gained by such a process. For a better understanding of the different sources and aspects of uncertainty, indeterminacy, vagueness, and the relations between them, a better understanding of the underlying ontological and epistemological foundations of imaging is necessary. An important aspect is to make the relationships between the objects in the world that are observed, for example, by means of remote sensing, and fiat objects created from the remote sensed data by means of spatial analysis explicit. Both kinds of objects are linked to each other by observation and analysis processes. The process of spatial analysis has three basic components which are modeled in this paper as mappings between fiat objects of different kind. We show that vagueness in the definition of fiat objects involved in this process results in indeterminacy of location of those objects. Definitorial vagueness and location indeterminacy of location result in uncertainty about the truth of conclusions about existence, properties, and location of objects in the world derived from knowledge about fiat objects created by spatial analysis.