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Présentation Uncertainty Modelling And Quality Control For Spatial Data Format Relié
- Livre Sciences de la vie et de la terre
Résumé : The rapid developments in GIS such as data integration and representation, spatial data products, and new spatial data mining methods, are forcing users to deal with data of unknown or ambiguous quality; thus, unpredictable risk in decision making is inevitable. This book covers aspects of spatial data quality that have been scarcely addressed. In the era of big data, the mass volume of heterogeneous data and the proper use of the acquired geospatial data remain a significant challenge for GIS users and need to be investigated.
Sommaire: 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.
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