Spatial analysis : statistics, visualization, and computational methods

316 Pages·2015·46.215 MB·English

by  Margai, Florence M., Oyana, Tonny J

Environmental Science
O Spatial Analysis
Spatial Analysis y
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Statistics, Visualization, and Computational Methods •
M Statistics, Visualization, and
“Right from the first page, this book reads differently. It’s not only the writing a
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style that is so different from your run-of-the-mill, dry statistical textbook, but also g Computational Methods
the combination of theoretical presentations with study questions and challenge a
i
assignments, making the reading so much more enjoyable while forcing the reader
to pause and reflect on the content of each chapter. Another feature of this book is
its breadth, encompassing the analysis of point, areal, and geostatistical data before
ending with a short chapter devoted to the hot topic of big data, including data
management and data mining. The illustration of different concepts using data from
environmental and social sciences adds to the general appeal of the presentation.
Tonny and Florence must be commended for writing a textbook that should make
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spatial analysis more accessible to geographers!”
—Pierre Goovaerts, BioMedware, Inc., PGeostat, LLC, p
University of Florida, Gainesville, USA
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“Spatial analysis is at the core of quantitative geography and geographic information
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systems (GIS). Oyana and Margai effectively explain the foundation of spatial
i
analysis. … The book provides a good balance between concepts and practicums of
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spatial statistics with a comprehensive coverage of the most important approaches to
understand spatial data, analyze spatial relationships and spatial patterns, and predict l
spatial processes. The book will be an excellent textbook for undergraduate courses
in quantitative geography or spatial analysis. Graduate students new to geospatial A
sciences will also find the book useful for self-study.”
—May Yuan, University of Texas at Dallas, USA n
a
An introductory text for the next generation of geospatial analysts and data scientists,
Spatial Analysis: Statistics, Visualization, and Computational Methods focuses l
on the fundamentals of spatial analysis using traditional, contemporary, and y
computational methods. Outlining both non-spatial and spatial statistical concepts,
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the authors present practical applications of geospatial data tools, techniques, and
strategies in geographic studies. They offer a problem-based learning (PBL) approach i
to spatial analysis—containing hands-on problem-sets that can be worked out in MS s
Excel or ArcGIS—as well as detailed illustrations and numerous case studies.
Tonny J. Oyana
K24901
6000 Broken Sound Parkway, NW Florence M. Margai
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Spatial Analysis
Statistics, Visualization, and
Computational Methods

Spatial Analysis
Statistics, Visualization, and
Computational Methods
Tonny J. Oyana
Florence M. Margai
CRC Press
Taylor & Francis Group
6000 Broken Sound Parkway NW, Suite 300
Boca Raton, FL 33487-2742
© 2016 by Taylor & Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
No claim to original U.S. Government works
Version Date: 20150702
International Standard Book Number-13: 978-1-4987-0764-0 (eBook - PDF)
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Visit the Taylor & Francis Web site at
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Spatial knowledge is boundless, so start your epic journey
now. Learn about geospatial data methods and tools and equip
yourself with practical skills in spatial analysis.
Tonny J. Oyana

Contents
Preface ...................................................................................................................xiii
Acknowledgments ................................................................................................xv
Authors ................................................................................................................xvii
1. Understanding the Context and Relevance of Spatial Analysis ...........1
From Data to Information, to Knowledge and Wisdom ............................5
Spatial Analysis Using a GIS Timeline .........................................................5
Spatial Analysis in the Post-1990s Period ................................................9
Geographic Data: Properties, Strengths, and Analytical
Challenges ............................................................................................................11
Concept of Scale ........................................................................................13
Concept of Spatial Dependency ..............................................................14
Concept of Spatial Proximity ..................................................................14
Modifiable Areal Unit Problem ...............................................................16
Concept of Spatial Autocorrelation ........................................................20
Conclusion ......................................................................................................23
Challenge Assignments ................................................................................23
Review and Study Questions .......................................................................24
Glossary of Key Terms ..................................................................................24
References .......................................................................................................25
2. Making Scientific Observations and Measurements in Spatial
Analysis ..........................................................................................................29
Scales of Measurement ..................................................................................30
Nominal Scale ............................................................................................30
Ordinal Scale .............................................................................................31
Interval Scale..............................................................................................32
Ratio Scale ..................................................................................................32
Two Main Approaches for Data Collection That Involve
Deductive and Inductive Reasoning .................................................34
Population and Sample .................................................................................37
Spatial Sampling .......................................................................................38
Conclusion ......................................................................................................52
Challenge Assignments ................................................................................52
Review and Study Questions .......................................................................53
Glossary of Key Terms ..................................................................................53
References .......................................................................................................54
vii
viii Contents
3. Using Statistical Measures to Analyze Data Distributions .................55
Descriptive Statistics .....................................................................................56
Measures of Central Tendency ................................................................57
Deriving a Weighted Mean Using the Frequency Distributions
in a Set of Observations ...........................................................................58
Measures of Dispersion ............................................................................59
Spatial Statistics: Measures for Describing Basic Characteristics
of Spatial Data ................................................................................................62
Spatial Measures of Central Tendency .......................................................64
Spatial Measures of Dispersion ...................................................................69
Random Variables and Probability Distribution .......................................71
Random Variable .......................................................................................71
Probability and Theoretical Data Distributions: Concepts
and Applications .......................................................................................71
Experiment I: Undertaking a Tossing Coin Activity ......................72
Experiment II: Undertaking the Rolling of a Die Activity .............72
Conclusion ......................................................................................................82
Challenge Assignments ................................................................................83
Review and Study Questions .......................................................................85
Glossary of Key Terms ..................................................................................85
References .......................................................................................................86
4. Engaging in Exploratory Data Analysis, Visualization, and
Hypothesis Testing .............................................................................................87
Exploratory Data Analysis, Geovisualization, and Data
Visualization Methods ..................................................................................88
Data Visualization .....................................................................................89
Geographic Visualization ........................................................................89
Exploratory Approaches for Visualizing Spatial Datasets ......................91
Visualizing Multidimensional Datasets: An Illustration Based
on the U.S. Educational Achievements Rates, 1970–2012 .......................102
Hypothesis Testing, Confidence Intervals, and p-Values .......................107
Computation ............................................................................................110
Statistical Conclusion .............................................................................110
Conclusion ....................................................................................................112
Challenge Assignments ..............................................................................113
Review and Study Questions .....................................................................117
Glossary of Key Terms ................................................................................117
References .....................................................................................................118
5. Understanding Spatial Statistical Relationships .................................121
Engaging in Correlation Analysis .............................................................121
Ordinary Least Squares and Geographically Weighted Regression
Methods .........................................................................................................126
Procedures in Developing a Spatial Regression Model.....................129