[ Order This Book ]
More Info:
Table of Contents

Casebook for Spatial Statistical Data Analysis : A Compilation of Analyses of Different Thematic Data Sets
Author: Griffith, Daniel A. / Sone, Akio
Cover: cover
List Price: $75.00
Published by Oxford University Press
Date Published: 08/1999
ISBN: 0195109589
Table of Contents
List of Data Sets Analyzed xv
Abbreviations xvi
PART I: THEORETICAL BACKGROUND
Introduction 3
Parallels between Spatial Autoregression 6
and Geostatistics
The Many Faces of Spatial Autocorrelation 9
The Moran Coefficient Scatterplot Tool 15
Multivariate Spatial Association 18
Heterogeneity and Locational Information 25
The Semivariogram Plot Tool 34
Computer Code for Implementing Spatial 39
Statistical Analyses
SAS Code for Computing MC Using Standard 62
Regression Techniques.
Directions for Using ArcInfo to Construct 64
a Thiessen Polygon Surface Partitioning
for a Set of Georeferenced Points.
SAS Macros Used for Converting among 67
Degrees, Decimal Degrees and Radians
Important Modeling Assumptions 69
The Relative Importance of the Principal 71
Assumptions
Variable Transformations 73
Transforming in Search of Normality 75
Transforming in Search of Constant Variance 79
Linearity: Exploitation of Linear 83
Relationships by Linear Statistical Models
An Absence of Independence: The Presence of 86
Spatial Autocorrelation in Georeferenced
Data
Exploring Residuals in Spatial Analysis 105
Other Statistical Frequency Distribution 111
Assumptions
Popular Spatial Autoregressive and 120
Geostatistical Models
Spatial Autoregressive Models 121
Geostatistical Models 133
Articulating Relationships Between Spatial 142
Autoregressive and Geostatistical Models
Computer Code for Spatial Autoregressive 153
and Semivariogram Modeling
SAS Code for Estimating Equations 165
(3.7ac)the CAR Model
SPSS Code for Estimating Equations 169
(3.7ac)the CAR Model
SAS Code for Estimating Equations (3.8) & 172
(3.9)the SAR & AR Models
SPSS Code for Estimating Equations (3.8) 175
& (3.9)the SAR & AR Models
SAS Code for Selected Semivariogram Models 178
SPSS Code for Selected Semivariogram 194
Models
PART II: GEOREFERENCED DATA SET CASE STUDIES 205
Analysis of Georeferenced Socioeconomic 207
Attribute Variables
The CliffOrd Eire Population Data 211
Urban Population Density 214
Residential Insurance Coverage in Chicago 218
Urban Crime in Columbus, Ohio 222
Geographic Distribution of Minorities 227
across Syracuse, New York
Concluding Comments: Spatial 232
Autocorrelation and Socioeconomic Attribute
Variables
Centroids Derived from a Digitized 234
Version of Cliff and Ord's Map of Eire
(1981, 207) Using ArcInfo
Analysis of Georeferenced Natural Resources 235
Attribute Variables
Kansas Oil Wells Data 241
Natural Resources Inventory Data 245
Island Biogeography: Plant Species Data 265
Weather Station Rainfall Data 272
Drainage Basin Runoff Data 277
Digital Elevation Data 284
Preclassified Remotely Sensed Image 292
Reflectance Data
Concluding Comments: Spatial 302
Autocorrelation and Natural Resources
Attribute Variables
Analysis of Georeferenced Agricultural Yield 305
Variables
The MercerHall Straw Yield Data 311
The Wiebe Wheat Yield Data 316
The Broadbalk Wheat and Straw Yield Data 320
Sugar Cane Production in Puerto Rico 330
Milk Production in Puerto Rico 337
Concluding Comments: Spatial 350
Autocorrelation and Agricultural Yield
Variables
Analysis of Georeferenced Pollution Variables 353
Southwestern Pennsylvania Coal Ash 360
EMAP Indicators of Ecological Condition 365
Great Smoky Mountains Water pH 373
Chemical Elements in Northwest Texas 378
Groundwater
Hazardous Waste Contamination of Soil: 390
Dioxin
Concluding Comments: Spatial 393
Autocorrelation and Pollution Variables
Analysis of Georeferenced Epidemiological 396
Variables
Glasgow Standardized Mortality Rates 405
Pediatric Lead Poisoning in Syracuse, New 410
York
Fox Rabies in Germany 417
Concluding Comments: Spatial 423
Autocorrelation and Epidemiological
Variables
PART III: VISUALIZING WHAT IS NOT OBSERVED 427
Exploding Georeferenced Data When Maps Have 428
Holes or Gaps: Estimating Missing Data Values
and Kriging
An Introduction to EM Estimation 430
Estimating Missing Values: Two Simplified 432
Georeferenced Data Illustrations
Estimating a Conspicuous Missing Data Value 438
for the CoalAsh Data Set
Estimating Conspicuous Missing Data Values 441
for an Agricultural Experiment
Estimating Missing Median Family Income 445
Data for OttawaHull
Generalizing a Map Surface with Kriging 447
A CrossValidation Example 451
Concluding Comments: Exploding 454
Georeferenced Data
Concluding Comments 457
More about the Nature of Georeferenced Data 459
Reflections on Spatial Data Model 460
Specifications
Implications regarding Relations between 469
Spatial Autoregressive and Geostatistical
Models
Reflections on Kriging 473
Spatial Statistics and GIS 475
Now Is the Time for All Good Spatial 476
Scientists to
Some Questions Yet Unanswered: Future 479
Research
Epilogue 484
References 488
Subject Index 503
