Uncertainty Modelling and Quality Control for Spatial Data

Offers New Insight on Uncertainty ModellingFocused 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 analysisSpatial statistical solutions in spatial data qualityEliminating systematic error in the analytical results of GIS applicationsA data quality perspective for GIS function workflow designData quality in multi-dimensional integrationResearch challenges on data quality in the integration and analysis of data from multiple sources A new approach for imprecision management in the qualitative data warehouseA multi-dimensional quality assessment of photogrammetric and LiDAR datasets based on a vector approachAn analysis on the uncertainty of multi-scale representation for street-block settlementUncertainty 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.