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Offers New Insight on Uncertainty Modelling Focused on major
research relative to spatial information, Uncertainty Modelling and
Quality Control for Spatial Data introduces methods for managing
uncertainties-such as data of questionable quality-in geographic
information science (GIS) applications. By using original research,
current advancement, and emerging developments in the field, the
authors compile various aspects of spatial data quality control.
From multidimensional and multi-scale data integration to
uncertainties in spatial data mining, this book launches into areas
that are rarely addressed. Topics covered include: New developments
of uncertainty modelling, quality control of spatial data, and
related research issues in spatial analysis Spatial statistical
solutions in spatial data quality Eliminating systematic error in
the analytical results of GIS applications A data quality
perspective for GIS function workflow design Data quality in
multi-dimensional integration Research challenges on data quality
in the integration and analysis of data from multiple sources A new
approach for imprecision management in the qualitative data
warehouse A multi-dimensional quality assessment of photogrammetric
and LiDAR datasets based on a vector approach An analysis on the
uncertainty of multi-scale representation for street-block
settlement Uncertainty Modelling and Quality Control for Spatial
Data serves university students, researchers and professionals in
GIS, and investigates the uncertainty modelling and quality control
in multi-dimensional data integration, multi-scale data
representation, national or regional spatial data products, and new
spatial data mining methods.
Offers New Insight on Uncertainty Modelling Focused on major
research relative to spatial information, Uncertainty Modelling and
Quality Control for Spatial Data introduces methods for managing
uncertainties-such as data of questionable quality-in geographic
information science (GIS) applications. By using original research,
current advancement, and emerging developments in the field, the
authors compile various aspects of spatial data quality control.
From multidimensional and multi-scale data integration to
uncertainties in spatial data mining, this book launches into areas
that are rarely addressed. Topics covered include: New developments
of uncertainty modelling, quality control of spatial data, and
related research issues in spatial analysis Spatial statistical
solutions in spatial data quality Eliminating systematic error in
the analytical results of GIS applications A data quality
perspective for GIS function workflow design Data quality in
multi-dimensional integration Research challenges on data quality
in the integration and analysis of data from multiple sources A new
approach for imprecision management in the qualitative data
warehouse A multi-dimensional quality assessment of photogrammetric
and LiDAR datasets based on a vector approach An analysis on the
uncertainty of multi-scale representation for street-block
settlement Uncertainty Modelling and Quality Control for Spatial
Data serves university students, researchers and professionals in
GIS, and investigates the uncertainty modelling and quality control
in multi-dimensional data integration, multi-scale data
representation, national or regional spatial data products, and new
spatial data mining methods.
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