Contributions to Spatial Uncertainty Modelling in GIS
Small Sample Data
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Environmental data is very costly and difficult to collect and are often vague or imprecise in nature. Fuzziness and small datasets leads to uncertainty, which is addressed by the research objective of this book: To model spatial environmental data with fuzzy uncertainty, and to explore the use of small sample data in spatial modelling predictions, within Geographic Information System (GIS). The methodologies underlying the theoretical foundations for spatial modelling are examined, such as geostatistics, fuzzy mathematics Grey System Theory, and Credibility Measure Theory. Fifteen papers incl...
Environmental data is very costly and difficult to collect and are often vague or imprecise in nature. Fuzziness and small datasets leads to uncertainty, which is addressed by the research objective of this book: To model spatial environmental data with fuzzy uncertainty, and to explore the use of small sample data in spatial modelling predictions, within Geographic Information System (GIS). The methodologies underlying the theoretical foundations for spatial modelling are examined, such as geostatistics, fuzzy mathematics Grey System Theory, and Credibility Measure Theory. Fifteen papers including three journal papers were written in contribution to the developments of spatial fuzzy and grey uncertainty modelling. The book is a particularly useful tool to postgraduate students and researchers, who work on uncertainty modelling, and with small sample spatial or GIS data.
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