Handbook of Geospatial Approaches to Sustainable Cities.

Format:

Book

Author/Creator:

Weng, Qihao.

Series:

Imaging Science Series

Language:

English

Subjects (All):

Sustainable urban development--Geographic information systems.

Sustainable urban development.

City planning--Environmental aspects.

City planning.

Urban ecology (Sociology).

Physical Description:

1 online resource (373 pages)

Edition:

1st ed.

Place of Publication:

Milton : Taylor & Francis Group, 2024.

Summary:

"This comprehensive handbook presents the current state of knowledge on geospatial technologies, techniques, and methods that are imperative for providing solutions to sustainable cities. It addresses the role of geospatial big data and AI techniques and how they are applied when analyzing the sustainability of urban development, land use, urban planning, and resource management, as well as monitoring the impact urbanization has on the environment and the ecosystem. With contributions from renowned experts around the world, this holistic handbook is a toolbox for geospatial, urban, and sustainability professionals, and the artificial intelligence community"-- Provided by publisher.

Contents:

Intro

Half Title

Series Page

Title Page

Copyright Page

Contents

Preface

PART I - Artificial Intelligence and Big Data Analytics: Needs and Requirements

PART II - Geospatial Techniques for Renewable Cities

PART III - Geospatial Techniques for Resilient Cities

PART IV - Digital Cities

Acknowledgments

Editors

Contributors

Part I: Artificial Intelligence and Big Data Analytics: Needs and Requirements

1. Sensing Urban Physical Environment with GeoAI and Street-Level Imagery

Introduction

Street-Level Imagery (SI)

Street-Level Imagery Sources

Street-Level Imagery Attributes

Methods for Sensing the Urban Physical Environment

Sensing Tasks

Scene Element Extraction

Scene Perception

Scene Inference

Scene Embedding

Scene Generation

Approaches Based on Techniques

Supervised Learning

Unsupervised Learning

Semi-Supervised Learning

Reinforcement Learning

Applications of Urban Sensing

Observational Sensing: Sensing the Physical Entity

Instance-Level Sensing

Street-Level Sensing

Neighborhood-Level Sensing

City-Level Sensing

Urban Implicit Relationship Sensing: Sensing Beyond the Image

Human Perception Sensing: Sensing with Human-Centric Perspective

Future Trends

References

2. Geospatial Big Data for Urban Sustainability Science

Urban Sustainability Science

Geospatial Big Data

Application of Using Geospatial Big Data

Agglomeration Economies

Urban Freight

Urban Functions and Transit-Oriented Development (TOD)

Conclusions

Future Challenges

3. Urban Flooding Monitoring and Management in Geospatial Perspective: Data, Techniques, and Platforms

Geospatial Data for Urban Flooding Monitoring

Geospatial Techniques for Urban Flooding Management.

Flood Modeling and Forecasting

Flood Mapping and Risk Assessment

Flooding Impact Assessment, Recovery, and Adaptation

Geospatial Platforms for Urban Flooding Management

Problems and Prospects

Data Availability and Quality Issues

Technical Limitations and Gaps

Geospatial Artificial Intelligence-Enabled Flood Monitoring and Management

Integration of Geospatial Platforms with Other Urban Management Systems

Part II: Geospatial Techniques for Renewable Cities

4. Assessing Sustainability in China's Resource-Based Cities: Leveraging Remote Sensing Techniques for Evaluating Environment-Related SDG Progress

Methods

City Categorization

Data Collection

Multi-criteria Decision Making

Results

Weight of SDG Indicators

Score of Each Environment-Related SDG

Overall Score of Environment-Related SDGs

Conclusion

5. Urban Green Space Maps Based on GeoAI

Introduction: Background and Driving Forces

GeoAI Method

Data Preprocessing

Multi-scale Feature Extraction Module

Multi-modal Information Fuse Module

Boundary Enhancement Module

Study Area and Datasets

Study Area

Datasets

Mapping Urban Green Spaces with Different Methods

6. Contrasting Pattern of Urban Expansion and Urban Land Use Intensification of Global Megacities using Nighttime Light Time Series Data

Time Series Modeling

Urban Built-Up Area Mapping

Urban Land Change Classification and Analysis

Urban Land Change Pattern

Discussions

7. The Potential of Nature-Based Solutions in Urban Heat Mitigation and Building Energy Savings

Introduction.

Nature-Based Solutions for Urban Heat Mitigation and Building Energy Savings

Green Roofs

Evaporative and Water-Retentive Pavements

Street Trees

Methodology

Assessment of Thermal Comfort

Mean Radiant Temperature

Outdoor Thermal Comfort Indices

Microclimatic Modeling

ENVI-met

Scenario Development

Validation of the Meteorological Outputs

Building Energy Simulation

EnergyPlus

Validation of the Building Energy Use

Performance of Nature-Based Solutions in Urban Heat Mitigation

Performance of Nature-Based Solutions in Building Energy Savings

Discussion

The Effectiveness of NBS in Cooling the Environment and Improving Thermal Comfort

The Effectiveness of Green Roofs in Reducing Building Energy Use

Part III: Geospatial Techniques for Resilient Cities

8. GeoAI for High-Resolution Urban Air Temperature Estimation and Urban Heat Island Monitoring

Study Area and Data

Satellite and In-Situ Meteorological Data

Local Climate Zone Map

Variable Processing

Air Temperature Estimation

Step 1: LST Downscaling

Step 2: Air Temperature Estimation

Urban Heat Islands Monitoring

Results and Discussion

LST Downscaling Results

Hourly Air Temperature Estimation Accuracy Assessment

Hourly Air Temperature Mapping Analysis

Diurnal Cycle of UHI Intensity

Novelty and Limitation

9. Satellite-Based Assessment of Urban Thermal Environments

Acquisition and Preprocessing of Satellite LST Data

Data Selection

Overview of LST Retrieval

Basic Theory

SC Algorithm

SW Algorithm

TES Algorithm

Urban-Specific LST Errors and Thermal Anisotropy

Scaling and Classification of LST

Evaluation of SUHI

Overall SUHII.

Simple SUHII with LULC

SUHII without LULC

SUHII based on Linear Relationship with Impervious Surface Area (ISA)

SUHII based on Gaussian Surface Model

SUHII Distribution

Quantifying Urban Growth

Diurnal Scale Analysis using Next-Generation Satellites

Challenges and Future Perspectives

10. Urban Air Pollution Mitigation for Sustainable Cities: Observation, Modeling, and Control Strategies

O3 and Its Primary Emitted Precursors

Airborne Particulate and Aerosols

Sampling Site Selection

Measurement Techniques

O3, CO, SO2 and NOx

VOCs

Online VOCs

Offline VOCs

OVOCs

SOA Tracers

VOCs Molecular Markers

NR-PM1 Compositions

Particle Size Distribution

Modeling and Calculation Techniques

Photochemical Box Model (PBM)

General Description

Simulation of Photochemical Pathways and Radicals

Estimate of Relative Incremental Reactivity (RIR)

Chemical Transport Model

Source Apportionment Model

Backward Particle Release Model

Quantification of Meteorological Impact

NPF-Related Calculations

Observations of Urban Air Pollutants

Intensive Samplings of Urban Air Pollutants

Characters of O3 and Its Precursors

Characters of VOCs

Chemical Compositions of Aerosols

Method Developing on AUFPs

Long-term Variations of Urban Air Pollutants

Numerical Simulations on Urban Air Pollution

Simulation of Atmospheric Dynamics

Simulation of Atmospheric Chemistry

Source Apportionments of Urban Air Pollutants

VOC Source Identification

Source Apportionment on OA

Control Strategies on Urban Air Pollution

Potential Control Measures for O3 Pollution

O3-Precursor Relationship

O3 Control Measures on Cutting Ratios of VOCs and NOx.

Source Contribution to VOCs and O3 Production

Aerosol Control Measures

11. Geospatial Analysis of Emerging Drought Risk in a Warming Climate

Spatiotemporal Evolution of Flash Drought

Underlying Mechanism of Flash Drought

Drought-related Compound Extremes

Summary and Conclusions

12. Urban Summer Air Temperature Forecasting through a Fusion of a Numerical Weather Prediction Model with Machine Learning

Machine Learning Algorithms

Machine Learning

Deep Learning

Overview of Study Area and Numerical Weather Prediction Model for Case Studies

Study Area: Seoul

Local Data Assimilation and Prediction System Model

Case Study 1: Machine Learning-based Spatial Distribution Production of Bias-corrected Urban Air Temperature Forecast

Data

Method

Case Study 2: Deep Learning-based Post-processing of Urban Air Temperature Forecast

Part IV: Digital Cities

13. GIS-Based Modeling for Estimating Urban Carbon Emissions

Data Sources and Methodologies for GIS-based Emissions Modeling

Top-Down Method Using Nighttime Lights

Bottom-Up Method

Hybrid Method

Cross-Comparison of the Methods

Case Studies of GIS-based Modeling for Urban Carbon Emissions Estimation

Modeling Spatiotemporal Carbon Emissions for Two Mega-Urban Regions

Research Steps

Spatiotemporal Carbon Emissions

Modeling High-resolution of Carbon Emissions for Two Mega-Urban Regions

Model Description

Spatial Distribution of Urban Carbon Emissions

Challenges and Opportunities in GIS-based Emissions Modeling

References.

14. The Relationship between Visual Space and Elders' Mental Health within 15-Minute Life Circles Using SVIs: A Case Study of Beijing.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-04-002756-3

1-003-24456-4

1-04-002749-0

9781003244561

OCLC:

1427664114