Spatial Analysis and Spatial
Statistics for Research in
Geography, GIS and Earth Management
Special Lecture Series
Henan University
May and September, 2012
Dr. Ron Briggs
(call me Dr. Ron)
Professor Emeritus
The University of Texas at Dallas
1
Introducing the Lecture Series
Today, I will introduce the lecture series:
 Introduce myself
 Explain the goals of the lecture series
 Discuss fundamental research principles:
– the major steps of any research project
– the importance of the research objective
– the need to review the existing literature
 Introduce
a project that you can work on
2
Geography, GIS and Earth Management
Where
 Geography
– The science of location
– Where things are located, and why
 Geographic
Why
?
Information Science (GIS)
– Technologies for analysis of where and why
 Earth
Management
– Geography and GIS applied to the real world
This class is for you all!
3
Geography, GIS and Earth Management
(G-GIS-EM)
Description
Explanation
Application
Geography
GIS
Earth Management
This class is for you all!
4
Who am I?
Dr. Ronald Briggs (call me Dr. Ron)
 Professor Emeritus (retired!?)

– University of Texas at Dallas
Email: briggs@utdallas.edu or rbriggs@utdallas.edu
 Web: www.utdallas.edu/~briggs
 Office: Room 319

– Come and talk with me there
– My cell phone number is 18739962744
5
Personal (continued)

Born in Liverpool, England
– At the same time as The Beatles
6
 Moved
–
–
–
–
–
to the US in 1966
Ph.D. The Ohio State University, Columbus
First job at University of Texas at Austin
Moved to UT-Dallas in 1976
Director of computing (1982-1995)
Director of programs in GIS (1995-2008)
Columbus, Ohio
Dallas
Austin
Texas
7
 My
specialization is Urban Geography and GIS
Nanjing Rd, Shanghai
Rio de Janeiro, Brazil
Sydney, Australia
8
But I am also interested in the natural environment
North Island, New Zealand
But bust
Amazon Rain Forest, Brazil
British Virgin Islands, Caribbean
9
The Goals of the Lecture Series
10
Goal #1
 help
you conduct high quality research in
Geography and Geographic Information
Systems
 describe standard research practices and
procedures in western countries
11
Goal #2: Improve your English.
 By
talking in English about some GIS
concepts you already know
 and some that you don’t know
 hopefully, I can provide some new insight
and understanding!
12
Goal #3: Learn about Spatial Statistics
n
n
n
n
  w ij (x i  x)(x j  x)/  w ij
i 1 j1
Centrographic Statistics
i 1 j1
n
 (x
i 1
i
 x)
n
n
2
 (x
i 1
i
 x) 2
n
Spatial Autocorrelation
 We
will focus on Spatial Analysis in
general, and Spatial Statistics in particular.
 Hopefully, you already know at least
something about spatial statistics
 Talking about it again here will help your
English, and help you better understand
13
spatial analysis and spatial statistics
Goal #4: Learn about doing
research on the U.S.
 Learn
about data sets for the United States
 Learn about geographical concepts used
with US data, for example
– Coordinate systems such as the State Plane
Coordinate System
– Geographic units used for reporting data such
as Metropolitan Statistical Areas (MSA),
census tracks, census blocks, etc.
14
Research in geography, GIS and
Earth Management
 Types
of Research
 Spatial analysis—the focus of my lectures
 The steps of a research project
 The importance of the research objective
 Using and citing the Existing Literature
15
Types of research in G-GIS-EM
1.
Data set generation
•
2.
Technology or tool development
•
3.
Often what you do for your first job!
Usually at universities or computer companies
Spatial Analysis
•
•
identifying spatial patterns
understanding why they occur
?
but all are interrelated
16
Research Interrelationships
Data
generation
used for
uses
Technology or
tool development
Spatial Analysis
Explanation
17
Example: Urban tree inventory
Fang Qiu, Jie Chang , Caiyun Zhang at UT-Dallas
 Urban
forests (trees in cities) very important
resource today
 Need inventory of trees by tree species
– Data generation
 Interpolation
and cluster analysis techniques used
to identify trees and their species
– Tool development and spatial analysis
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Interpolation and cluster analysis techniques applied
to remote sensing data used to identify tree species

Ground Points
Accuracy doubled from existing methods:
--60%-70% versus 30%-40%
Urban tree inventory:
relevant to all your areas of study
 Physical
geography
– Trees are an important part of the natural environment
– Biogeography and forestry
 Economic
geography
– Trees are an important economic resource $
– significantly increase the value of houses and land
 GIS
– GIS tools and techniques required to do the inventory
 Earth
Management
– Trees are a critical resource to be managed
21
Example: cancer data
(source: Rogerson and Yamada p. 17, from Cuzick and Edwards, 1990)
(data is for childhood cancer in northern England)
Location of children with cancer
--they appear to cluster
(concentrated in one area)
Why?
--because people cluster in
cities?
--because there is a source of
pollution?
Need to apply spatial analysis to examine if cancer cases
still cluster after we remove the obvious factor that people
cluster in cities.
Briggs Henan University 2010
The focus of the my lectures
23
This lecture series will focus on tools and
techniques for spatial analysis
 The
−
−
goal of spatial analysis is to
Describe and identify spatial patterns, and
understand why they occur
 Spatial
analysis usually
– states a hypothesis: a guess at a possible explanation
 e.g.
Environmental pollution results in higher rates of disease
– designs a study to test that hypothesis using
 Appropriate
data
 Appropriate tools and techniques
 Spatial
statistics are often the best tools to use
– We will focus on spatial statistics
– See Outline of Lecture Topics
24
Outline of Lecture Topics: Spring (May)
Week 1 (May 7)
1. Research Methodology: The Central Role of Goals and Objectives. (1Intro.ppt)
2. Spatial Analysis: Concepts and Issues (2spatanal.pp)
3. Spatial Data: What is special about spatial data? (3spatdata.pp)
Week 2 (May 14)
4. Standard Statistics & Spatial Statistics: Differences & Similarities (5CentroStat.ppt)
5. Descriptive Spatial Statistics for Points and Polygons
6. Inferential Spatial Statistics: Standard and spatial (6InfStat.pp)
Week 3 (May 21)
7. Point Pattern Analysis: Concepts and Tests for Clustering and Dispersion
(7.1PointPat.pp)
8. Point Pattern Analysis: Applied Point Pattern Analysis (7.2PointPat.ppt)
9. Conclusion and preview of September classes: Analyzing polygons and surfaces
25
Outline of Lecture Topics (Fall)
Week 4 (Fall- 1st week)
10. Review of May sessions (Point Patterns) and Intro to fall (Polygons & Surfaces)
11. Spatial Autocorrelation: concept and implementation (9SAconcepts.pp)
12. Global Measures of Spatial Autocorrelation: Moran’s I and Geary’s C
(10SAglobal.ppt)
Week 5(Fall-2nd week)
13. Local measures of Spatial Association: Anselin’s LISA & others (11SALocal.ppt)
14. Using GeoDA for measuring spatial autocorrelation (12SADemo.pp)
15. Regression and Correlation: standard approach (13SpatReg.pp)
Week 6 (Fall-3rd week)
16. Spatial Regression
17. Using GeoDA for standard and spatial regression (15Regdemo.pp)
18. Analyzing surfaces: Concepts and Trend Surface Analysis (18Surfaces.pp)
Week 7 (Fall-4th week)
19. Analyzing surfaces: IDW and Kriging
18. Research at UT-Dallas: spatial statistics in practice. (16UTDRes.ppt)
19. A taste of other topics: cluster creation, network analysis, interaction data 26
Software
(training will be included)
 ArcGIS
from ESRI, Inc. (licensed)
 GeoDA by Luc Anselin, Arizona State
University (freely available)
http://geodacenter.asu.edu/software/downloads
 Crime Stat III by Ned Levine, National Institute
for Criminal Justice (freely available)
http://www.icpsr.umich.edu/CrimeStat/download.html
Copies also on my web site at:
www.utdallas.edu/~briggs
27
Research projects:
what must be included.
US students seldom get this right.
You must do better!!!
28
The seven parts of every Research Project

Objective, explains the purpose of the research and why it is
important
– Usually includes Hypotheses: possible explanations which you will test






Literature Review, identifies the key pieces of existing research
relevant to the project and the hypotheses
Data Sources, identifies and explains the data used.
Analysis and Methodology, explains the methodology applied to
the data.
Results, describes the main research findings, whether or not the
hypotheses were upheld, and any potential problems or
shortcomings
Conclusion, discusses the implications of your results relative to
your initial project objective.
References, provide standard format citations for all resources
used in the project.
For more detail, go to:
http://www.utdallas.edu/~briggs/poec6389/gisc6389_contents.doc
29
•
•
These 7 parts are necessary for every research
project
Every research paper or report should include a
section covering each part
30
 Which
component do you spend the most time
on in your courses?
–Data and methods!!
 Which
component is the most important for
successful research?
–The objective and the hypotheses
Objective: the foundation for
any research project
31
Objective
Everything depends on the objective
 Hypotheses
are based upon the objective
 data is selected which enables you to test the
hypotheses and meet your objective
 methods of analysis are applied to the data in
order to meet your objective
 Your results and conclusions are always made
relative to your objective
Everything links back to the objective!
32
Objective: one sentence
Example (project you can do):
 This research is in the area of environmental
justice.
 Environmental justice is concerned with whether or
not some groups of people are more exposed to
environmental hazards than other groups
 “The objective of this research is to examine if low
income or ethnic minorities in Dallas, Texas are
more exposed to pollution than higher income
groups or non-minorities”
33
Objective—your guide for everything!
Your guide for every research decision
 What hypothesis will meet my objective?
 What data is needed to meet my objective?
 Which analytical method(s) is best to meet
my objective?
 How are my results relevant to my
objective?
If it doesn’t relate to the objective, don’t do it!
34
The Literature Review
All research and analysis should build
upon the existing base of knowledge
 Must use the existing base of knowledge to:

Base of Knowledge
– Identify appropriate objectives
– State logical hypotheses
– Select and use correct methodologies and appropriate data

All of this is accomplished by reviewing the existing
literature
 of
scientific knowledge published in refereed journals
 not a Baidu or Google search
35
Help with Literature Reviews
A standard Baidu or Google search is not sufficient! Instead, use Google Scholar
• http://scholar.google.com/
The single most commonly used academic bibliographic database in US is probably
“Web of Science” at
• http://isi10.isiknowledge.com/portal.cgi?DestApp=WOS&Func=Frame
• Your library may provide access
A very useful bibliography fro GIS from ESRI is
• http://training.esri.com/campus/library/index.cfm
Lists of GIS journals are available
• On website of Dr Fang Qiu
– http://www.utdallas.edu/~ffqiu/
• On my web site (with other information about GIS)
– http://www.utdallas.edu/~briggs/other_gis.html
36
How to Format Citations
• It is very important to use the correct format when citing literature
– copying/pasting a URL is not sufficient!
– It may be gone tomorrow
• The Chicago Manual of Style is the accepted norm.
The Chicago Manual of Style. Chicago: University of Chicago Press,
15th ed., 2003
– Or, copy the format used by any major journal in your field
• Good summaries of correct formatting are available at:
– http://www.libs.uga.edu/ref/chicago.html
– Or , http://library.osu.edu/help/research-strategies/citereferences/chicago-author-date/
• References are usually listed in a section at the end of the paper
– For powerpoint presentations, it is good also to include the full
citation on the slides where it is discussed
– A person reading a paper can "flip to the end" to check a
reference, but a listener cannot do that with a presentation!37
Texts
O’Sullivan, David and David Unwin, 2010.
Geographic Information Analysis. Hoboken, NJ:
John Wiley, 2nd ed.
Other Useful Books:
Mitchell, Andy 2005. ESRI Guide to GIS Analysis Volume 2: Spatial
Measurement & Statistics. Redlands, CA: ESRI Press.
Allen, David W 2009. GIS Tutorial II: Spatial Analysis Workbook.
Redlands, CA: ESRI Press.
Wong, David W.S. and Jay Lee 2005. Statistical Analysis of Geographic
Information. Hoboken, NJ: John Wiley, 2nd ed.
38
Example Project
You do it!
Hypothesis Testing using
ArcMap
39
www.utdallas.edu/~briggs
40
ArcMap Project
Zip file (proj1_data.zip)
Word document (proj1.doc)
Purpose:
 Example of spatial analysis with objective,
hypotheses, etc.
 Experience with US data
ArcMap project
41
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