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Uncertainty Modelling and Quality Control for Spatial Data

Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9781498733342
Veröffentl:
2015
Seiten:
308
Autor:
Shi Wenzhong
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
2 - DRM Adobe
Sprache:
Englisch
Beschreibung:

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
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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