Advances in Geocomputation (eBook)

Dr. Daniel A. Griffith is an Ashbel Smith Professor of Geospatial Information Sciences at the University of Texas at Dallas, chair of the International Spatial Accuracy Research Association (ISARA) Steering Committee, a Committee member of the International Geographical Union (IGU) Commission on Modeling Geographical Systems Steering, an elected Regional Science Association International (RSAI) Councilor, a two-appointment Fulbright Senior Specialist, and an elected fellow of the American Association for the Advancement of Science (AAAS), the American Statistical Association (ASA), the Spatial Econometrics Association, the RSAI, and the New York Academy of Sciences. He also is a former Guggenheim fellow, and has been awarded distinguish scholarship honors by the Association of American Geographers. Dr. Griffith has published nearly two dozen books and over 200 papers, and is a previous editor of Geographical Analysis.Dr. Yongwan Chun is an associate professor of Geospatial Information Sciences at the University of Texas at Dallas. His research interests lie in spatial statistics and GIS, focusing on urban issues concerning population movement, environment, health, and crime. His research has been supported by the US National Science Foundation and the US National Institutes of Health, among others. He has over 50 publications, including books, journal articles, book chapters, conference proceedings, and encyclopedia entries. He served on the Geocomputation (2015) and Spatial Statistics (2013) international conference organizing committees.Dr. Denis J. Dean is the Dean of the School of Economic, Political and Policy Sciences and a former Head of the Geospatial Information Sciences program at the University of Texas at Dallas.  He has taught courses in spatial optimization, geospatial modeling and analysis,remote sensing, cartography, geodesy and other aspects of geospatial information sciences to students in North and South America, Europe and Asia.  He has published over 75 papers on spatial optimization, accuracy assessment of common spatial analysis operators, and other areas of geospatial information science.  

Preface 6
The Symposium Series, the Venue, and the Conference Program 7
Contents 12
1 Introduction 16
1 Concluding Comments 17
2 The Nexus of Food, Energy, and Water Resources: Visions and Challenges in Spatial Computing 19
Abstract 19
1 Introduction 20
2 A Spatial Computing Vision 23
2.1 FEW Observations 24
2.2 FEW Data Management 24
2.3 FEW Data Mining 25
2.4 Decision Support 26
2.5 FEW Data Visualization 27
3 Spatial Computing Challenges 27
3.1 FEW Observation Challenges 27
3.2 FEW Data Management Challenges 28
3.3 FEW Data-Mining Challenges 29
3.4 FEW Decision Support Challenges 30
3.5 FEW Data Visualization Challenges 31
4 Summary 31
Acknowledgements 32
References 32
3 The Bird’s-Eye View from a Worm’s-Eye Perspective 35
Abstract 35
1 Introduction 35
2 Ups and Downs 37
3 Ins and Outs 39
4 Before and After 39
5 Here and There 42
6 Corners and Curves 43
7 Conclusion 44
References 45
Spatial Data: Construction, Representation, and Visualization 46
High-Resolution Population Grids for the Entire Conterminous United States 47
1 Introduction 47
2 Data and Methods 49
2.1 The Gen-1 Disaggregation Method 50
2.2 The Gen-2 Disaggregation Method 50
3 Results 51
4 Conclusions 56
References 57
5 A Hybrid Dasymetric and Machine Learning Approach to High-Resolution Residential Electricity Consumption Modeling 59
Abstract 59
1 Introduction 60
2 Related Work 60
3 Methodology 61
4 Application and Results 63
4.1 Datasets 63
4.2 Results and Discussion 64
5 Conclusion 68
Acknowledgements 69
References 69
6 Can Social Media Play a Role in the Development of Building Occupancy Curves? 71
Abstract 71
1 Introduction 72
2 Unit Occupancy 73
3 Social Media Unit Occupancy 74
4 Results 75
5 A Model-Based Research Agenda 75
Acknowledgment 77
References 77
7 Application of Social Media Data to High-Resolution Mapping of a Special Event Population 79
Abstract 79
1 Introduction 80
2 Methods and Results 80
3 Discussion 85
Acknowledgements 85
References 85
8 Animating Maps: Visual Analytics Meets GeoWeb 2.0 87
Abstract 87
1 Introduction 87
2 Literature Review 88
3 System Design 89
3.1 Mode of Operation 89
3.1.1 Automatic Mode 89
3.1.2 User Customization Mode 91
3.2 System Architecture 91
3.2.1 User Interface 92
3.2.2 Server 93
3.2.3 Map API 93
3.2.4 Database 93
4 Results 93
5 Conclusion 95
References 95
9 Atvis: A New Transit Visualization System 97
Abstract 97
1 Introduction 97
2 Atvis Visualization Model 99
2.1 Goals and Objectives 99
2.2 Atvis Model Design 99
3 An Atvis Visualization Demonstration Program 100
3.1 Data Description 101
3.2 Backend System 101
3.3 The Frontend System 102
3.4 Visualization Methodologies 106
3.4.1 The Display Method 106
3.4.2 The Arc Normalization Method 106
3.4.3 The Arc Scaling Algorithm 106
4 Discussion/Conclusion 107
References 107
10 Mapping Spatiotemporal Patterns of Disabled People: The Case of the St. Jude’s Storm Emergency 109
Abstract 109
1 Introduction 110
2 Data 111
2.1 The Oyster Card System 111
2.2 A Case Study 112
2.3 Choosing Covariates 113
2.3.1 Opportunities/Destinations 113
2.3.2 PTAL 114
3 Methods 115
3.1 Data Preparation 115
3.2 Defining the Spatial Neighborhood 116
3.3 Modeling 117
4 Results 119
5 Conclusions 121
6 Limitations and Future Work 122
References 123
11 Terra Populus: Challenges and Opportunities with Heterogeneous Big Spatial Data 126
Abstract 126
1 Introduction 126
2 Terra Populus 127
3 Terra Populus User Interface 128
4 Terra Populus’s High-Performance Architecture 129
4.1 Microdata Integration 129
4.2 High-Performance Computation of Vector and Raster Data 130
5 Conclusion 131
References 132
Spatial Analysis: Methods and Applications 133
12 A Deviation Flow Refueling Location Model for Continuous Space: A Commercial Drone Delivery System for Urban Areas 135
Abstract 135
1 Introduction 136
2 Route Derivation: A Convex Path Algorithm 136
3 Distance-Restricted Maximal Coverage Location Model 138
4 A Heuristic Solution Technique: Simulated Annealing with a Greedy Algorithm 139
5 Application Results 140
6 Conclusions 141
References 141
13 Exploring the Spatial Decay Effect in Mass Media and Location-Based Social Media: A Case Study of China 143
Abstract 143
1 Introduction 143
2 Datasets 144
2.1 The Main Dataset: GDELT 145
2.2 Complementary Datasets 146
3 Methodology and Preliminary Results 147
3.1 Data Preprocessing 147
3.2 Model Construction 147
4 Conclusion 150
References 151
14 Uncovering the Digital Divide and the Physical Divide in Senegal Using Mobile Phone Data 153
Abstract 153
1 Introduction 153
2 Methods 154
3 Results 156
3.1 The Digital Divide 156
3.2 The Physical Divide 157
4 Conclusions 160
References 161
15 Application of Spatio-Temporal Clustering For Predicting Ground-Level Ozone Pollution 162
Abstract 162
1 Introduction 163
2 Method 163
3 Dataset 164
4 Data Mining 167
5 Ozone Forecasting 172
6 Conclusion 175
References 175
16 Does the Location of Amerindian Communities Provide Signals About the Spatial Distribution of Tree and Palm Species? 177
Abstract 177
1 Introduction 178
2 Methodology 179
2.1 The Study Area 179
2.2 Collection of Spatial and Attribute Data About Multiple-Use Plants 180
2.3 Designing the Spatial Dataset 182
3 Results 182
4 Discussion/Conclusions 185
5 Future Work 186
Acknowledgements 186
References 187
World Climate Search and Classification Using a Dynamic Time Warping Similarity Function 188
1 Introduction 188
2 Data and Methods 189
2.1 Data Source 190
2.2 Data Preprocessing 190
2.3 Variables and Their Normalization 190
2.4 Dissimilarity Measure 192
2.5 Clustering Methods and CCs Comparisons 194
3 Climate Classifications 195
4 Climate Search 198
5 Conclusions 201
References 202
18 Attribute Portfolio Distance: A Dynamic Time Warping-Based Approach to Comparing and Detecting Common Spatiotemporal Patterns Among Multiattribute Data Portfolios 203
Abstract 203
1 Introduction 204
2 Dynamic Time Warping 204
3 Attribute Portfolio Distance 206
4 Trend Only Attribute Portfolio Distance 206
5 Application and Results 207
6 Summary 209
Acknowledgements 210
References 211
19 When Space Beats Time: A Proof of Concept with Hurricane Dean 212
Abstract 212
1 Introduction 213
2 A Case Study: The Yucatan Peninsula—NDVI Before and After Hurricane Dean 214
3 Methods and Data 214
3.1 Data 215
3.2 Methods: Temporal and Spatial Models 216
3.3 Model Performance Assessment 216
4 Results 217
5 Conclusion and Discussion 219
References 220
20 Using Soft Computing Logic and the Logic Scoring of Preference Method for Agricultural Land Suitability Evaluation 221
Abstract 221
1 Introduction 222
2 Context of the Case Study 222
3 The Logic Scoring of Preference Method 223
4 LSP Land Suitability Maps 227
5 Conclusion 229
Acknowledgements 230
References 230
21 Surgical Phase Recognition using Movement Data from Video Imagery and Location Sensor Data 232
Abstract 232
1 Introduction 233
2 Data Collection 234
2.1 Video Imagery 234
2.2 Ultrasonic Location Aware System 234
3 Methods 235
3.1 Tag Movements 235
3.2 Optical Flow 236
3.3 Trajectory Clustering 236
4 Results 237
5 Discussion 238
Acknowledgements 239
References 239
Spatial Statistical and Geostatistical Modeling 241
22 Respondent-Driven Sampling and Spatial Autocorrelation 242
Abstract 242
1 Introduction 243
2 Data 243
2.1 Network 243
2.2 Demographics 244
2.3 Transformation and Mapping 245
2.4 Spatial Autocorrelation 245
3 Methodology 248
3.1 Network Chains 248
3.2 Simulation Design 248
4 Anticipated Results 248
Acknowledgements 249
Appendix 249
References 251
23 The Moran Coefficient and the Geary Ratio: Some Mathematical and Numerical Comparisons 253
Abstract 253
1 Introduction 253
2 The Relationship Between the MC and GR 254
3 Derivation of the MC and GR Asymptotic Variances 255
4 Efficiency Analysis 257
4.1 Normal Variance Ratios 259
4.2 Uniform Variance Ratios 260
4.3 Beta Variance Ratios 262
4.4 Exponential Variance Ratios 262
4.5 Variance Ratio Convergence 264
5 A Power Comparison 265
5.1 Establishing Statistical Power 265
5.2 Theoretical Evaluation 267
6 Conclusions 268
References 269
24 A Variance-Stabilizing Transformation to Mitigate Biased Variogram Estimation in Heterogeneous Surfaces with Clustered Samples 270
Abstract 270
1 Introduction 270
2 Methodology 272
2.1 Data 272
2.2 The Box–Cox Transformation and Kriging Prediction 273
3 Results 277
4 Conclusions 278
References 279
Estimating a Variance Function of a Nonstationary Process 280
1 Introduction 280
2 Data Model and Variance Function Estimator 281
2.1 Data Model 281
2.2 Notation and Definitions 282
2.3 A Variance Function Estimator 284
3 Exploring Filter Options and an Application 285
3.1 The Filter Configuration and Weights 285
3.2 Simulation Set-up 286
3.3 Results and Recommendations 287
3.4 An Empirical Example 290
4 Conclusions 291
References 292
26 The Statistical Distribution of Coefficients for Constructing Eigenvector Spatial Filters 293
Abstract 293
1 Introduction 293
2 Eigenvector Spatial Filtering 294
3 Methodology 294
4 A Simulation Experiment 295
5 Results 296
6 Implications 299
Acknowledgements 300
References 300
27 Spatial Data Analysis Uncertainties Introduced by Selected Sources of Error 301
Abstract 301
1 Introduction 301
2 Literature Review 302
3 Data and Simulation Experiments 303
3.1 Location Error Simulation Experiment Design 303
3.2 Measurement Error Simulation Experiment Design 305
4 Results 306
4.1 Location Error 306
4.2 Measurement Error 306
5 Findings and Future Research 308
Acknowledgements 310
References 310
28 Spatiotemporal Epidemic Modeling with libSpatialSEIR: Specification, Fitting, Selection, and Prediction 312
Abstract 312
1 Introduction 312
2 Stochastic Compartmental Models 313
3 Software 315
4 Analysis 315
5 Impact 319
References 319
29 Geostatistical Models for the Spatial Distribution of Uranium in the Continental United States 321
Abstract 321
1 Introduction 321
2 Methods 323
3 Results 324
4 Conclusions 329
Acknowledgements 330
References 330
30 Modeling Land Use Change Using an Eigenvector Spatial Filtering Model Specification for Discrete Responses 331
Abstract 331
1 Introduction 331
2 Multinomial Autologistic Regression for Land Suitability Analysis 332
3 Estimation Method 333
4 Study Area and Data 334
5 Results 336
5.1 The Nonspatial MNL Model 337
5.2 The Spatial MNL Model 338
6 Conclusion 339
References 339
Computational Challenges and Advances in Geocomputation: High-Performance Computation and Dynamic Simulation 341
31 From Everywhere to Everywhere (FETE): Adaptation of a Pedestrian Movement Network Model to a Hybrid Parallel Environment 342
Abstract 342
1 Introduction 342
2 Proposed Solution 344
3 Results 345
4 Conclusions 347
Acknowledgements 347
References 348
32 Parallelizing Affinity Propagation Using Graphics Processing Units for Spatial Cluster Analysis over Big Geospatial Data 349
Abstract 349
1 Introduction 349
2 The Affinity Propagation Program 351
3 Computation Constraints in the AP Program 353
4 Parallelization of the AP Program 354
5 Implementation of the Parallelized AP Program with the GPU 355
6 Conclusion 357
Acknowledgments 358
Appendix 1 358
Appendix 2 361
References 362
33 A Web-Based Geographic Information Platform to Support Urban Adaptation to Climate Change 364
Abstract 364
1 Introduction 365
2 The Urban-CAT Framework 366
2.1 Framework 367
2.2 Methods 368
3 Some Initial Results 371
4 Conclusion 372
Acknowledgements 373
References 373
34 A Fully Automated High-Performance Image Registration Workflow to Support Precision Geolocation for Imagery Collected by Airborne and Spaceborne Sensors 375
Abstract 375
1 Introduction 375
2 Core Development Concepts 376
3 Registration Workflow 376
3.1 Preprocessing 377
3.2 Trusted Source Selection 379
3.3 Global Localization 379
3.4 Image Registration 380
3.5 Sensor Model Resection and Uncertainty Propagation 382
3.6 A Note About Spatial Uncertainty 382
3.7 Enhanced Metadata Generation 383
4 Initial System Performance Metrics 384
5 Conclusion 385
Acknowledgements 385
References 385
35 MIRAGE: A Framework for Data-Driven Collaborative High-Resolution Simulation 387
Abstract 387
1 Introduction 388
2 Methods and Data 388
3 Model Execution and Work in Progress 392
4 Conclusion and the Next Steps 394
Acknowledgements 394
References 394
36 A Graph-Based Locality-Aware Approach to Scalable Parallel Agent-Based Models of Spatial Interaction 396
Abstract 396
1 Introduction 397
2 Literature Review 397
2.1 Spatially Explicit Agent-Based Models 397
2.2 Locality of Reference 398
3 A Locality-Aware Approach 400
3.1 The Locality Principle 400
3.2 Locality-Aware Computational Domain 400
4 Design and Experimentation of Parallel SE-ABMs 402
4.1 Agent-Based Spatial Interaction Model 402
4.2 Homogeneous Neighborhoods 403
4.3 Heterogeneous Neighborhoods 404
4.4 Locality-Aware Parallel Models on Shared-Memory Platforms 405
5 Results and Discussion 407
5.1 Homogeneous Interaction 407
5.2 Heterogeneous Interaction 410
6 Conclusions and Future Work 411
References 412
37 Simulation of Human Wayfinding Uncertainties: Operationalizing a Wandering Disutility Function 415
Abstract 415
1 Introduction 415
2 Definitions 416
3 The Research Problem 416
4 Background 417
4.1 Quantifying Dementia 417
4.2 Spatial Orientation and Human Wayfinding 418
4.3 Wandering Behavior 419
4.4 Observation and Simulation of Human Movement and Wandering 419
5 Methods 420
6 Expected Results 422
7 Conclusion 422
References 424
38 Design and Validation of Dynamic Hierarchies and Adaptive Layouts Using Spatial Graph Grammars 426
Abstract 426
1 Introduction 427
2 Theory and Methodology 427
2.1 Dynamic Hierarchies with Emergence 428
2.2 Modeling with Multiple Representations 429
2.3 Adapting to Layout Context with Spatial Semantics 429
3 Implementation 430
4 Conclusion and Discussion 433
Acknowledgements 434
References 434