Quality aspects in spatial data mining

Substantial 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 imprecise, allowing for much interpretation of abstract figures and data. Quality Aspects in Spatial Data Mining introduces practical and theoretical solutions for making sense of the often chaotic and overwhelming amount of concrete data available to researchers.

In this cohesive collection of peer-reviewed chapters, field authorities present the latest field advancements and cover such essential areas as data acquisition, geoinformation theory, spatial statistics, and dissemination. Each chapter debuts with an editorial preview of each topic from a conceptual, applied, and methodological point of view, making it easier for researchers to judge which information is most beneficial to their work.

Chapters Evolve From Error Propagation and Spatial Statistics to Address Relevant Applications

The book advises the use of granular computing as a means of circumventing spatial complexities. This counter-application to traditional computing allows for the calculation of imprecise probabilities - the kind of information that the spatial information systems community wrestles with much of the time.

Under the editorial guidance of internationally respected geoinformatics experts, this indispensable volume addresses quality aspects in the entire spatial data mining process, from data acquisition to end user. It also alleviates what is often field researchers' most daunting task by organizing the wealth of concrete spatial data available into one convenient source, thereby advancing the frontiers of spatial inf

Author Notes

Alfred Stein, Wenzhong Shi, Wietske Bijker

Alejandro Pauly and Markus SchneiderAndrew FrankSven SchadeMohamed Bakillah and Mir Abolfazl Mostafavi and Yvan Bedard and Jean BrodeurAna-Maria OlteanuHaixia Mao and Wenzhong Shi and Yan TianRodrigo Manzione and Martin Knotters and Gerard Heuvelink and Jos von Asmuth and Gilberto CamaraGerhard NavratilRangsima Sunila and Karin KolloSytze de Bruin and Gerard Heuvelink and James BrownMarco Marinelli and Robert Corner and Graeme WrightMartin Vermeer and Karin KolloRene R. Colditz and Christopher Conrad and Thilo Wehrmann and Michael Schmidt and Stefan DechFelix Hebeler and Ross S. PurvesArief Wijaya and Prashanth R. Marpu and Richard GloaguenEkatarina S. Podolskaya and Karl-Heinrich Anders and Jan-Henrik Haunert and Monika SesterTom H.M. Rientjes and Tamiru H. AlemsegedAlexis J. Comber and Pete F. Fisher and Alan BrownAbdelbasset Guemeida and Robert Jeansoulin and Gabriella SalzanoEduardo S. Dias and Alistair J. Edwardes and Ross S. PurvesAnna T. Boin and Gary J. HunterKerstin Huth and Nick Mitchell and Gertrud SchaabAlex M. Lechner and Simon D. Jones and Sarah A. BekessyPaul WatsonMichael F. Goodchild

Foreword	p. ix
Contributing Authors	p. xi
Introduction	p. xvii
Section I Systems Approaches to Spatial Data Quality
Introduction	p. 1
Chapter 1 Querying Vague Spatial Objects in Databases with VASA	p. 3
Chapter 2 Assessing the Quality of Data with a Decision Model	p. 15
Chapter 3 Semantic Reference Systems Accounting for Uncertainty: A Requirements Analysis	p. 25
Chapter 4 Elements of Semantic Mapping Quality: A Theoretical Framework	p. 37
Chapter 5 A Multicriteria Fusion Approach for Geographical Data Matching	p. 47
Section II Geostatistics and Spatial Data Quality for DEMs
Introduction	p. 57
Chapter 6 A Preliminary Study on Spatial Sampling for Topographic Data	p. 59
Chapter 7 Predictive Risk Mapping of Water Table Depths in a Brazilian Cerrado Area	p. 73
Chapter 8 Modeling Data Quality with Possibility Distributions	p. 91
Chapter 9 Kriging and Fuzzy Approaches for DEM	p. 101
Section III Error Propagation
Introduction	p. 115
Chapter 10 Propagation of Positional Measurement Errors to Field Operations	p. 117
Chapter 11 Error Propagation Analysis Techniques Applied to Precision Agriculture and Environmental Models	p. 131
Chapter 12 Aspects of Error Propagation in Modern Geodetic Networks	p. 147
Chapter 13 Analysis of the Quality of Collection 4 and 5 Vegetation Index Time Series from MODIS	p. 161
Chapter 14 Modeling DEM Data Uncertainties for Monte Carlo Simulations of Ice Sheet Models	p. 175
Section IV Applications
Introduction	p. 197
Chapter 15 Geostatistical Texture Classification of Tropical Rainforest in Indonesia	p. 199
Chapter 16 Quality Assessment for Polygon Generalization	p. 211
Chapter 17 Effectiveness of High-Resolution LIDAR DSM for Two-Dimensional Hydrodynamic Flood Modeling in an Urban Area	p. 221
Chapter 18 Uncertainty, Vagueness, and Indiscernibility: The Impact of Spatial Scale in Relation to the Landscape Elements	p. 239
Chapter 19 A Quality-Aware Approach for the Early Steps of the Integration of Environmental Systems	p. 251
Chapter 20 Analyzing and Aggregating Visitor Tracks in a Protected Area	p. 265
Section V Communication
Introduction	p. 283
Chapter 21 What Communicates Quality to the Spatial Data Consumer?	p. 285
Chapter 22 Judging and Visualizing the Quality of Spatio-Temporal Data on the Kakamega-Nandi Forest Area in West Kenya	p. 297
Chapter 23 A Study on the Impact of Scale-Dependent Factors on the Classification of Landcover Maps	p. 315
Chapter 24 Formal Languages for Expressing Spatial Data Constraints and Implications for Reporting of Quality Metadata	p. 329
Epilogue: Putting Research into Practice	p. 345
Index	p. 357

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