Quality Aspects in Spatial Data Mining
Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data QualitySubstantial progress has been made toward developing effective techniques for spatial information processing in recent years. This science deals with models of reality in a GIS, however, and not with reality itself. Therefore, spatial information processes are often impre
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Quality Aspects in Spatial Data Mining
Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data QualitySubstantial progress has been made toward developing effective techniques for spatial information processing in recent years. This science deals with models of reality in a GIS, however, and not with reality itself. Therefore, spatial information processes are often impre
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Quality Aspects in Spatial Data Mining

Quality Aspects in Spatial Data Mining

Quality Aspects in Spatial Data Mining

Quality Aspects in Spatial Data Mining

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Overview

Describes the State-of-the-Art in Spatial Data Mining, Focuses on Data QualitySubstantial progress has been made toward developing effective techniques for spatial information processing in recent years. This science deals with models of reality in a GIS, however, and not with reality itself. Therefore, spatial information processes are often impre

Product Details

ISBN-13: 9781040206607
Publisher: CRC Press
Publication date: 04/19/2016
Sold by: Barnes & Noble
Format: eBook
Pages: 374
File size: 14 MB
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About the Author

Alfred Stein, Wenzhong Shi, Wietske Bijker

Table of Contents

Granular Computing - Computing with Uncertain, Imprecise, and Partially True Data, Systems Approaches to Spatial Data Quality. Querying Vague Spatial Objects in Databases with VASA. Assessing the Quality of Data with a Decision Model. Semantic Reference Systems Accounting for Uncertainty: A Requirements Analysis. Elements of Semantic Mapping Quality: A Theoretical Framework. A Multicriteria Fusion Approach for Geographical Data Matching. Geostatistics and Spatial Data Quality for DEMs. A Preliminary Study on Spatial Sampling for Topographic Data. Predictive Risk Mapping of Water Table Depths in a Brazilian Cerrado Area. Modeling Data Quality with Possibility Distributions. A Comparison of Geostatistics and Fuzzy Applications for Digital Elevation Models. Error Propagation. Propagation of Positional Measurement Errors to Field Operations. Error Propagation Analysis Techniques Applied to Precision Agriculture and Environmental Models. Aspects of Error Propagation in Modern Geodetic Networks. Analysis of the Quality of Collection 4 and 5 Vegetation Index Time Series from MODIS. Modeling DEM Data Uncertainties for Monte Carlo Simulations of Ice Sheet Models. Applications. Geostatistical Texture Classification of Tropical Rainforest in Indonesia. Quality Assessment for Polygon Generalization. Effectiveness of High-Resolution LIDAR DSM for Two-Dimensional Hydrodynamic Flood Modeling in an Urban Area. Uncertainty, Vagueness, and Indiscernibility: The Impact of Spatial Scale in Relation to the Landscape Elements. A Quality-Aware Approach for the Early Steps of the Integration of Environmental Systems. Analyzing and Aggregating Visitor Tracks in a Protected Area. Communication. What Communicates Quality to the Spatial Data Consumer? Judging and Visualizing the Quality of Spatio-Temporal Data on the Kakamega-Nandi Forest Area in West Kenya. A Study on the Impact of Scale-Dependent Factors on the Classification of Landcover Maps. Formal Languages for Expressing Spatial Data
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