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Guiding Principles

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Guiding Principles COMPUTATIONAL AND VISUAL ANALYSES OF SPATIAL INTERACTIONS: A CASE STUDY OF THE COUNTY-TO-COUNTY MIGRATION IN THE US by Ke Liao Bachelor of Science Lanzhou University, 1998 Master of Science Northern Illinois University, 2004 Submitted in Partial Fulfillment of the Requirements For the Degree of Doctor of Philosophy in Geography College of Arts and Sciences University of South Carolina 2011 Accepted by: Diansheng Guo, Major Professor Susan L. Cutter, Committee Member Michael E. Hodgson, Committee Member Linyuan L. Lu, Committee Member Tim Mousseau, Dean of The Graduate School UMI Number: 3469151 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMI 3469151 Copyright 2011 by ProQuest LLC. All rights reserved. This edition of the work is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI 48106-1346 © Copyright by Ke Liao, 2011 All Rights Reserved. ii ACKNOWLEDGEMENTS My sincerest gratitude goes to my advisor, Dr. Diansheng Guo. By being a magnificent example, he taught me what research and what doing research are about. His passion, insights, and persistence to high standards have been the resources I count on. Thank him for his great guidance throughout this dissertation process. His advising and encouragement has made this dissertation possible. I would also like to express my thankfulness toward my great committee, Dr. Susan Cutter, Dr. Michael Hodgson, and Dr. Linyuan Lu for their help and patience. I am in debt to them for their huge support in agreeing me to serve on my committee. I thank faculty members in this department for teaching me, directly and indirectly. I am also grateful to the staff here for their wonderful assistance. My thanks are extended to Hai Jin, Caglar Koylu, Peng Gao, and Hu Wang for their amazing help on data preparation, programming, and their inspirations. I am thankful for my family in China, my husband, and my precious son. My husband has provided support as much as he could. My son often “delighted” me by pulling me away from my computer desk. I thank them for their love. iii ABSTRACT Spatial interactions (SI), such as human daily movements, disease spread, and commodity flows, are among the essential forces that drive many physical and socioeconomic processes. Spatial interactions are very complex in nature. A normal SI data set often contains three different data spaces: the geographic space, the graph/network space, and the multivariate space. The goal of this research is to address the underutilization and the underrepresentation of SI data. Currently there is a lack of powerful exploratory analytic methods that can deal with the complexity of spatial interactions, which often involve: (1) multiple data spaces, (2) various spatial constraints, (3) many variables for locations and interactions (flows), and (4) the large data size. It is unlikely that an individual method alone can fully address these challenges. This dissertation develops an integrated computational-visual approach to examining SI data from different perspectives and synthesizing different perspective views into a holistic understanding. The contribution of this research is two-fold. First, it develops a graph partitioning method to discover spatially contiguous community patterns (SI regions). Evaluations with benchmark data indicate that the developed method is more effective and more computationally efficient than traditional methods. Second, this research uses SI regions as a data aggregation strategy to summarize massive spatial flows. It combines the three SI data spaces in data iv exploration and representation. SI regions, multivariate patterns, and geographic patterns of SI flows are analyzed simultaneously in a novel and interactive visual analytic system. A large inter-county migration data set of the U.S. is used to assess the developed approach and implemented visual analytic system from an application perspective. The data contains over 700,000 county-to-county migration flows (i.e., origin–destination pairs). The results demonstrate that the SI regions obtained by analyzing the spatial information and network connections can unveil real-world structures such as the strong “core-suburban relationship” from a network perspective. A focused study on income migration shows that the developed integrative approach is able to synthesize the various data spaces, address the high-dimensions, and cope with the large size of SI data. The combination of graph partition, multivariate visualization, flow mapping, and interactive interfaces creates a flexible, comprehensive, and efficient environment to explore SI data from different perspectives and obtain holistic understandings. This reported approach facilitates new and comprehensive analyses that existing research methodologies cannot support. v TABLE OF CONTENTS ACKNOWLEDGEMENTS ........................................................................................................ iii ABSTRACT .......................................................................................................................... iv LIST OF TABLES ................................................................................................................ viii LIST OF FIGURES ................................................................................................................. ix CHAPTER 1 INTRODUCTION ...............................................................................................1 1.1 BACKGROUND AND MOTIVATION ....................................................................................... 3 1.2 AN INTEGRATED APPROACH ............................................................................................... 7 1.3 CASE STUDY ..................................................................................................................... 10 1.4 THE ORGANIZATION OF THE DISSERTATION ..................................................................... 11 CHAPTER 2 2000 CENSUS COUNTY-TO-COUNTY DOMESTIC MIGRATION DATA .......12 2.1 OVERVIEW OF THE DATA .................................................................................................. 12 2.2 DATA PROCESSING............................................................................................................ 18 CHAPTER 3 GRAPH PARTITIONING OF SPATIAL INTERACTIONS ............................... 21 3.1 REVIEW OF GRAPH PARTITIONING .................................................................................... 22 3.2 NEW SPATIALLY-CONSTRAINED GRAPH PARTITIONING METHOD..................................... 39 3.3 EVALUATIONS AND COMPARISONS................................................................................... 50 3.4 SUMMARY AND DISCUSSIONS .......................................................................................... 57 CHAPTER 4 VISUAL EXPLORATION OF FLOW PATTERNS .......................................... 60 4.1 MAPPING SI FLOWS: RELATED WORK ............................................................................... 61 4.2 AN INTEGRATED AND INTERACTIVE ANALYSIS ENVIRONMENT ....................................... 72 4.3 AN ILLUSTRATION ............................................................................................................ 83 4.4 SUMMARY AND DISCUSSIONS .......................................................................................... 90 CHAPTER 5 CASE STUDY: 1995-2000 DOMESTIC MIGRATIONS IN THE U.S. ................ 93 5.1 BACKGROUND: MIGRATION STUDIES ................................................................................ 94 5.2 NETWORK-DERIVED SI REGIONS ....................................................................................... 96 5.3 INCOME MIGRATION IN THE U.S. .................................................................................... 106 5.4 SUMMARY AND DISCUSSIONS ......................................................................................... 129 CHAPTER 6 CONCLUSIONS. .......................................................................................... 132 vi REFERENCES .....................................................................................................................135 vii LIST OF TABLES Table 2.1. Attribute fields of the outflow data files provided by the 2000 Census ...........15 Table 2.2. Stratifications of the 2000 Census migration data. ...........................................18 Table 3.1. Comparative analyses of IPFP-SLK and the Intramax approach. ....................29 Table 3.2 Configurations of GN and LFR graphs..............................................................37 Table 3.3. Procedures of the contiguity-constrained graph partitioning method ...............41 Table 3.4. Graph partitioning methods for SI data considered in the evaluation ..............53 Table 3.5. Configurations of example and evaluation graphs ...........................................53 Table 3.6. The time cost of methods tested on the GN benchmark graphs .......................57 Table 3.7. The time cost of methods tested on the LFR benchmark graphs ......................57 Table 4.1. The functions of the components in the visual system. ....................................75 Table
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