Geospatial Data Analytics and Urban Applications (Advances in 21st Century Human Settlements)

Preface
Acknowledgements
Contents
Contributors
Abbreviations
Spatial Big Data and Urban Analytics: An Introduction
	1 Introduction
	2 Global Challenges and Spatial Data
	3 Spatial Big Data Science
		3.1 Workflow
		3.2 Spatial Analytics
		3.3 Algorithms
	4 Urban Applications
		4.1 Smart Sensors and Smart Cities
		4.2 Applications in This Book
Preferential Home Search in Urban Settings
	1 Introduction
		1.1 HDB Towns in Singapore
		1.2 Amenities Within Walking Distance
		1.3 Searching for Property
	2 Study Objectives
		2.1 Objectives
		2.2 Scope
	3 Data and Methodology
		3.1 Data Types and Sources
		3.2 Methodology
	4 Results
		4.1 Closest Facility Analysis
		4.2 Improvement Analysis
	5 Discussion
		5.1 Simulation Dashboard
		5.2 Limitations
		5.3 Conclusions
	References
Air Quality Dynamics and Urban Heat Island Effects During COVID-19
	1 Introduction
		1.1 Objectives
		1.2 Study Area
	2 Data and Methods
		2.1 Data
		2.2 Methodology
	3 Results
		3.1 Spatial Analysis of Covid-19
		3.2 Air Quality Dynamics
		3.3 Urban Heat Island (UHI) Effects
	4 Discussion
	References
Mass Rapid Transit and Population Dynamics During Covid-19 in Singapore
	1 Introduction
		1.1 MRT Ridership and Urban Development
		1.2 Influence of Covid-19 Restrictions
	2 Objectives, Data and Methods
		2.1 Objectives
		2.2 Data and Sources
		2.3 Framework
		2.4 Algorithms Used
	3 Analysis and Results
		3.1 Typology Classification of MRT Stations
		3.2 Popularity Analysis
		3.3 Popularity Patterns and Variations
		3.4 Outlier Analysis
	4 Discussion
		4.1 Open Space and MRT Station Popularity
		4.2 Re-opening Policy and Passenger Volume
		4.3 Conclusions and Limitations
	References
A Geospatial Analysis of Tweets During Post-circuit Breaker in Singapore
	1 Introduction
	2 Methodology
		2.1 Data Collection
		2.2 Spatio-Temporal Analysis
		2.3 Random Forest Model
	3 Analysis and Results
		3.1 Twitter Users in Singapore
		3.2 Distribution in Space and Time
		3.3 Regression Analysis
		3.4 Modelling Using Random Forest Classifier
	4 Discussion
		4.1 Activity Patterns and Relations to Service Amenities and Land Use
		4.2 Limitations
	5 Conclusion
	References
Space–Time Analytics of New York City Shooting Incidents
	1 Introduction
		1.1 Study Area
		1.2 Objectives and Scope
		1.3 Data and Sources
	2 Methodology
		2.1 Data Wrangling
		2.2 Analysis
	3 Results and Discussion
		3.1 Shooting Incidents in Space and Time
		3.2 Regression Analysis
		3.3 Network Analysis
	4 Conclusions
		4.1 Limitations
	References
Spatial and Temporal Patterns of Tourist Source Market Emissiveness: A Study of Shanghai, China
	1 Introduction
		1.1 Emissiveness and Tourism
		1.2 Objective and Scope
		1.3 Methodology and Workflow
		1.4 Definitions
	2 Data and Pre-processing
		2.1 Yearbook
		2.2 Scenic Spots
		2.3 Travel Demand Index
	3 Methods of Analysis
		3.1 Spatial Analysis of Destination Attraction
		3.2 Travel Demand Index Pattern Evolution
		3.3 Spatial Analysis of Emissiveness in Tourist Source Markets
	4 Results
		4.1 Spatial Distribution and Tourist Score
		4.2 Travel Demand Index Patterns
		4.3 Emissiveness in Tourist Source Markets
	5 Conclusions
		5.1 Limitations
		5.2 Future Scope
	References
Spatial Perspectives of Crime Patterns in Chicago Amid Covid-19
	1 Introduction
		1.1 Study Area
	2 Methodology
	3 Analysis and Results
		3.1 Crime Trends
		3.2 Trends by Type
		3.3 Reasoning High Crime Rates
	4 Discussion and Conclusion
	References
Geospatial Analysis of Grab Trips in Singapore
	1 Introduction
		1.1 Study Area
		1.2 Objective and Scope
	2 Data Used
		2.1 Grab Posisi
		2.2 Point of Interest (POI) Dataset
		2.3 Resident Population Data
	3 Methodology
		3.1 Units of Spatial Analysis
		3.2 Multiple Collinear Diagnosis and Global Regression
		3.3 Spatial Autocorrelation
		3.4 Geographical Weighted Regression(GWR)
		3.5 Multi-scale Geographic Weighted Regression (MGWR)
	4 Results
		4.1 Regression Analysis
		4.2 GWR and MGWR Results
	5 Conclusion
		5.1 Limitations
	References
Ecological Vulnerability of Nyingchi, Tibet
	1 Introduction
		1.1 Objectives and Scope
		1.2 Data
	2 Methodology
		2.1 Data Screening and Pre-processing
		2.2 Analytical Methods
	3 Analysis and Results
		3.1 Ecological Vulnerability
		3.2 Spatial Variability of EVSI
		3.3 EVSI Change Trends
		3.4 Analysis of Hotspots
	4 Discussion
		4.1 Role of Natural Factors
		4.2 Role of Anthropogenic Factors
		4.3 Ecological Vulnerability and Sustainable Development
	5 Conclusion
	References