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 Dataserves 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.
Table of Contents
UNCERTAINTY MODELLING AND QUALITY CONTROL. Uncertainty-Related Research Issues in Spatial Analysis. Spatial Statistical Solutions in Spatial Data Quality to Answer Agricultural Demands Based on Satellite Observations. Eliminating Systematic Error in Analytical Results of GIS Applications. Function Workflow Design for Geographic Information System: A Data Quality Perspective. UNCERTAINTIES IN MULTIDIMENSIONAL AND MULTISCALE DATA INTEGRATION. Data Quality in the Integration and Analysis of Data from Multiple Sources: Some Research Challenges. Quality Management of Reference Geo-Information. A New Approach of Imprecision Management in Qualitative Data Warehouse. Quality Assessment in River Network Generalisation by Preserving the Drainage Pattern. QUALITY CONTROL FOR SPATIAL PRODUCTS. Quality Control of DLG and Map Products. VGI for Land Administration: A Quality Perspective. Qualitative and Quantitative Comparative Analysis of the Relationship between Sampling Density and DEM Error by Bilinear and Bicubic Interpolation Methods. Automatic Method of Inspection for Deformation in Digital Aerial Imagery Based on Statistical Characteristics. Comparison of Point Matching Techniques for Road Network Matching. UNCERTAINTIES IN SPATIAL DATA MINING. Towards a Collaborative Knowledge Discovery System for Enriching Semantic Information about Risks of Geospatial Data Misuse. Uncertainty Management in Seismic Vulnerability Assessment Using Granular Computing Based on Neighborhood Systems. Increasing the Accuracy of Classification Based on Ant Colony Algorithm.
Wenzhong Shi, Bo Wu, Alfred Stein