Tài liệu hạn chế xem trước, để xem đầy đủ mời bạn chọn Tải xuống
1
/ 465 trang
THÔNG TIN TÀI LIỆU
Cấu trúc
Cover
Geospatial Analysis and Modelling of Urban Structure and Dynamics
The GeoJournal Library
ISBN 9048185718
Foreword
A Coming of Age: Geospatial Analysis and Modelling in the Early Twenty First Century
Acknowledgments
Authors Biographies
Editors
Contributors
Contents
Contributors
Part 1: Introduction
Geospatial Analysis and Modeling of Urban Structure and Dynamics: An Overview
1.1 GIS = GISystems, GIScience, GIServices and GIStudies
1.2 Individual-Based Data Capture for Modeling Urban Structure and Dynamics
1.3 Modeling Urban Complexity and Hierarchy
1.4 Simulating and Modeling Urban Transportation Systems
1.5 Analyzing and Modeling Urban Growth, Urban Changes and Impacts
1.6 Studying Other Urban Problem Using Geospatial Analysis and Modeling
1.7 Conclusion
References
Part 2: Individual-Based Data Capture for Modeling Urban Structure and Dynamics
High-Resolution Geographic Data and Urban Modeling: The Case of Residential Segregation
2.1 Introduction
2.2 The Potential Implications of High Resolution Data for Socio-geographic Research
2.3 Simulation of Social Residential Segregation
2.4 Discussion and Conclusions
References
Space Syntax and Pervasive Systems
3.1 Introduction
3.2 Space Syntax
3.2.1 Operationalisation
3.2.1.1 Axial Maps
3.2.1.2 Metrics
3.2.2 Data Collection and Observation
3.2.2.1 Data Sources
3.2.2.2 Gatecounts
3.2.2.3 Static Snapshots
3.2.2.4 Trails
3.2.3 Empirical Results
3.2.4 Criticism
3.3 Pervasive Systems and Space Syntax
3.4 Case Studies
3.4.1 Space Syntax and Application Development
3.4.2 Space Syntax as an Explanatory Tool
3.4.3 Space Syntax as a Modelling Tool
3.5 Conclusion and Ongoing Work
References
Decentralized Spatial Computing in Urban Environments
4.1 Introduction
4.2 Related Work
4.2.1 The City in Flux
4.2.2 Decentralized Spatial Computing
4.2.3 Safeguarding Privacy
4.3 Protecting Privacy with DeSC
4.3.1 An LBS Scenario
4.3.2 Experimental Methodology
4.4 Experiment #1: Quality of Service versus Level of Privacy
4.5 Experiment #2: Communication Network Effects
4.6 Experiment #3: Goal Directed Movement
4.7 Experiment #4: Push and Pull Queries
4.8 Conclusions and Outlook
References
Part 3: Modeling Urban Complexity and Hierarchy
Network Cities: A Complexity-Network Approach to Urban Dynamics and Development
5.1 Introduction
5.2 Methodology
5.3 The Model
5.4 Analysis
5.4.1 The Parameter PV0
5.4.2 The Parameter beta
5.4.3 The Parameter PT
5.5 Conclusions
References
Scaling Analysis of the Cascade Structure of the Hierarchy of Cities
6.1 Introduction
6.2 Models and Principles
6.2.1 Mathematical Models
6.2.2 Basic Principles
6.3 Data Processing Methods and Empirical Evidences
6.3.1 City Classification Based on Urban Numbers
6.3.2 City Classification Based on Population Sizes
6.4 Applications and Discussions
6.4.1 Symmetry Analysis of the Two Classification Results for Regional Studies
6.4.2 Analysis of Spatial Interactions in Urban Studies
6.4.3 Town Classification in the Small-Scaled Region
6.5 Concluding Remarks
6.6 Appendix
6.6.1 The Concept of ``City'' in China at Present
6.6.2 The Equivalence Relation Between the 2n Rule and the Rank-Size Rule with an Exponent -1
References
Part 4: Simulating and Modeling Urban Transportation Systems
The Dilemma of On-Street Parking Policy: Exploring Cruising for Parking Using an Agent-Based Model
7.1 Introduction
7.2 Parking Models
7.3 The PARKAGENT Model
7.3.1 Infrastructure GIS
7.3.2 Driver Agents and Their Behavior
7.3.3 Driver's Decision to Park on the Way to Destination
7.3.4 Cruising for Parking
7.3.5 Algorithm of Car Following
7.3.6 Technical Characteristics of the Model
7.4 Non-spatial (Point) Model of Parking
7.5 Cruising for Commercial Parking
7.6 Cruising Threshold
7.7 Effects of Space on Cruising
7.7.1 Equal Arrival and Egress Rates
7.7.2 When the Point Approximation Becomes Sufficient?
7.8 Conclusions
References
Multiscale Modeling of Virtual Urban Environments and Associated Populations
8.1 Introduction
8.2 Our VUE Design Pattern
8.2.1 Locations
8.2.2 Transport Network
8.2.3 Places/Transport Network Relationships
8.2.4 Illustration
8.3 Example of Creating a Multiscale VUE: The Case of Quebec-City
8.4 The Synthetic Population of Quebec-city
8.4.1 Estimation of Non-spatial Attributes
8.4.2 Allocation of Spatial Attributes
8.5 TransNetSIM: Using the Meso-VUE with Associated Synthetic Population for Simulating Travel Activities
8.5.1 Pre-processing Data for TransNetSIM
8.5.2 Simulation of Trips Using TransNetSIM
8.5.3 TransNetSIM's Performance
8.6 Conclusion
References
Imageability and Topological Eccentricity of Urban Streets
9.1 Introduction
9.2 Topology of Urban Street Networks and Imageability
9.3 The Tel Aviv Street Network: Structural Qualities and Imageability
9.4 Conclusion
References
A Spatial Analysis of Transportation Convenience in Beijing: Users' Perception Versus Objective Measurements
10.1 Introduction
10.2 Literature Review
10.2.1 Urban Transportation and City Livability
10.2.2 UrbanTransportation Studies in China
10.3 Data Used for This Study
10.3.1 Residents' Perception of Transportation Convenience
10.3.2 Objective Measurements for Beijing's Urban Transportation
10.4 Methodology and Procedure
10.4.1 Subjective Scores for Urban Transportation Convenience
10.4.2 Objective Scores for Urban Transportation Convenience
10.4.3 Link the Perceived Transportation Convenience with the Measured
10.5 Analysis of Results
10.6 Discussion and Conclusions
References
Object-Oriented Data Modeling of an Indoor/Outdoor Urban Transportation Network and Route Planning Analysis
11.1 Introduction
11.2 Network Data Models
11.2.1 Modeling Multi-Modal Networks
11.2.2 3D Network Modeling
11.3 Modeling Transportation Networks in Urban Environments
11.3.1 Modeling Movement Inside Buildings
11.3.1.1 Conceptualizing the Floor Network
11.3.1.2 Modeling Movement Between Floors
11.3.2 Modeling Movement Outside Buildings
11.3.2.1 Modeling Multiple Modes
Street Network
Bus Routes
Walkways
Modeling Transfers Between Modes
11.4 Data Model Implementation
11.4.1 FloorNetwork
11.4.2 ExitPoints
11.4.3 FloorTurns
11.4.4 WalkWays
11.4.5 Streets
11.4.6 CampusBusRoutes
11.4.7 CampusBusStops
11.4.8 ParkingLotEntrance
11.4.9 Sidewalk_Busroute_Transfer
11.4.10 Streets_Walkways_Transfer
11.4.11 Creating the Network Dataset
11.5 Developing a 3D Path-Finding Application
11.5.1 Results from Path-Finding Analysis
11.5.1.1 Determining the Least-Effort Route Inside a Building
11.5.1.2 Determining a Least-Effort Route Between Two Buildings
11.5.1.3 Determining an ``All-Inside'' Least-Effort Route Between Two Buildings
11.6 Conclusions
References
Part 5: Analyzing and Modeling Urban Grown, Urban Changes and Impacts
Integration of Remote Sensing with GIS for Urban Growth Characterization
12.1 Introduction
12.2 Integrating Remote Sensing and GIS for Urban Growth Research
12.3 The Case Study Site
12.4 Data Acquisition, Processing and Analysis
12.4.1 Data Acquisition and Assemblage
12.4.2 Image Processing of Remotely Sensed Data
12.4.3 Change Detection
12.4.4 Spatial Statistical Analysis
12.4.5 Predictive Modeling and Simulation
12.5 Urban Spatial Growth
12.6 Urban Growth and Landscape Change Driving Forces
12.6.1 High-Density Urban Use
12.6.2 Low-Density Urban Use
12.7 Future Urban Growth Scenario Simulation
12.8 Conclusions
References
Evaluating the Ecological and Environmental Impact of Urbanization in the Greater Toronto Area through Multi-Temporal Remotely Sensed Data and Landscape Ecological Measures
13.1 Introduction
13.2 Method
13.2.1 Study Area
13.2.2 Data Sets
13.2.3 Landscape Ecological Measures
13.3 Results and Analysis
13.4 Conclusions
References
Modeling Urban Effects on the Precipitation Component of the Water Cycle
14.1 Introduction and Motivation
14.2 Historical and Current Perspectives on the Urban Rainfall Effects
14.3 Modeling Studies of the Urban Rainfall Effect
14.4 Atlanta and Houston Case Studies
14.4.1 Atlanta
14.4.1.1 Model Configuration and Approach
14.4.1.2 Results
14.4.2 Houston
14.4.2.1 Configuration and Approach
14.4.2.2 Results
14.5 Recommendations to Improve Model Studies of the Urban Rainfall Effect
14.6 Current and Future Advances in Modeling Urban Effects on Precipitation
References
Interpolating a Consumption Variable for Scaling and Generalizing Potential Population Pressure on Urbanizing Natural Areas
15.1 Introduction
15.2 Scales of Urbanization
15.3 Approach for the Analysis
15.3.1 Related Literature
15.3.2 Study Area
15.3.3 Data Sources and Analysis
15.4 Results
15.5 Conclusions
References
Modeling Cities as Spatio-Temporal Places
16.1 Introduction
16.2 Time and Spatio-Temporal Modeling
16.3 Spatio-Temporal Ontology for Places
16.4 A Spatio-Temporal Model for Places
16.4.1 Some Modeling Issues
16.4.1.1 Vagueness and Identity
16.4.1.2 Granularity of Space, Time, and Processes
16.4.2 Spatio-Temporal Place Model
16.5 Analyzing Spatio-Temporal Relationship
16.6 Discussions and Future Research
References
Part 6: Studying Other Urban Problems Using Geospatial Analysis and Modeling
Geospatial Analysis and Living Urban Geometry
17.1 Introduction
17.2 Networks of Urban Space in a Living City
17.3 Geospatial Analysis and ``Urban Seeding''
17.4 Useful and Useless Urban Space
17.5 Urban Complexity and Modular Decomposition
17.6 Three Different Metaphors for a City
17.7 Do We Wish to Connect to Our Neighbor?
17.8 Respecting and Re-creating Complex Urban Fabric
17.9 The Problem of Designing the City's Periphery
17.10 Spatio-Temporal Scale Jumps and Their Implications
17.11 Spontaneous Settlements: What We Can Learn from Them
17.12 Conclusion
References
Analyzing Spatial Patterns of Late-Stage Breast Cancer in Chicago Region: A Modified Scale-Space Clustering Approach