Remote Sensing of Urban and Suburban Areas (Remote Sensing and Digital Image Processing, 10)

"Remote Sensing of Urban and Suburban Areas" provides instructors with a text reference that has a logical and easy-to-follow flow of topics around which they can structure the syllabi of their urban remote sensing courses. Topics have been chosen to bridge the gap between remote sensing and urban studies through a better understanding of the science that underlies both fields. In so doing, the book includes 17 chapters written by leading international experts in respected fields to provide a balanced coverage of fundamental issues in both remote sensing and urban studies. Emphasis is placed on: theoretical and practical issues in contemporary urban studies and remote sensing; the spectral, spatial and temporal requirements of remotely sensed data in relation to various urban phenomena; methods and techniques for analyzing and integrating remotely sensed data and image processing with geographic information systems to address urban problems; and examples of applications in which applying remote sensing to tackle urban problems is deemed useful and important. This book will be of interest to university instructors, advanced undergraduate students, graduate students, and researchers in the fields of geography, architecture, engineering and urban planning. - Logical and easy-to-follow flow of topics around which university instructors can structure the syllabuses of their urban remote sensing courses - Set-up of chapters contains educational aids such as learning objectives, summarizing text boxes, exercises and learning activities at the end of each chapter. Chapter 1: Urban and Suburban Areas as a Research Topic for Remote Sensing 1.1 Introduction 1.2 Introduction to the Chapters References Part I Theoretical Aspects Chapter 2: The Structure and Form of Urban Settlements 2.1 Urban Structure and Urban Growth: An Overview of Theories and Methodologies 2.2 Physical Manifestations of Urban Growth: Suburbanization and Sprawl 2.2.1 Defining Sprawl Through Form 2.2.2 Defining Sprawl Through Land Use 2.3 The SCATTER Project 2.3.1 Qualitative Analysis of Urban Sprawl in Europe 2.3.2 Statistical Indicators to Identify and Quantify Urban Sprawl 2.4 Conclusions References Chapter 3: Defining Urban Areas 3.1 What Is Urban? 3.2 Urban–Rural Is Not Really a Dichotomy 3.3 Remotely-Sensed Data as Proxies for the Built Environment 3.3.1 What Spatial Unit of Analysis Should Be Used? 3.3.2 What Variables Should Be Used to Define Urbanness? 3.3.3 How Will the Variables Be Measured? 3.4 Using the Urban Index as a Predictor Variable References Chapter 4: The Spectral Dimension in Urban Remote Sensing 4.1 Introduction 4.2 Spectral Characteristics of Urban Surfaces 4.3 Urban Materials Versus Land Cover Types 4.4 Spectral Separability of Urban Land Cover Types 4.5 Most Suitable Wavelengths in Mapping Urban Land Cover 4.6 Effects of Spectral Resolution on Urban Land Cover Mapping 4.7 Effects of Spatial Resolution and Three-Dimensional Information References Chapter 5: The Spatial and Temporal Nature of Urban Objects 5.1 Introduction 5.2 Planning and Management of Urban Development 5.2.1 A Model of Urban Development and Planning 5.3 Basic Objects, Attributes, and Planning Level 5.4 Area-Based and Object-Based Approaches to Urban Data Extraction 5.5 Data Sources for Urban Applications 5.5.1 Selection of an Appropriate Resolution 5.6 The Life Cycle of Planning Processes and Urban Objects 5.7 Implications for Urban Applications of Remote Sensing References Chapter 6: The V-I-S Model: Quantifying the Urban Environment 6.1 Introduction 6.2 The V-I-S Model 6.2.1 Relationship to Urban Spatial Models 6.2.2 Time and Change 6.2.3 The Role of Remote Sensing in Urban Systems 6.3 The Influence of Resolution on V-I-S Analysis 6.4 Morphological Application of the V-I-S Model 6.4.1 SPOT-X Data: Spatial Variation in Urban Communities 6.4.2 IRS-1C Data: Anatomy of a Metropolis 6.4.3 Thematic Mapper Data: Multivariate Calibration and Color Display 6.4.4 Thematic Mapper Data: Radial Transects for Environmental Patterns 6.4.5 AVIRIS Data: Neural Network Analysis 6.5 Environmental Process Application of the V-I-S Model 6.5.1 ATLAS Data: Thermal Emittance per Land Cover Class 6.5.2 Thematic Mapper/SPOT-P Data: Storm Runoff Prediction 6.6 Temporal Application of the V-I-S Model 6.6.1 SPOT-X Data: Pre- and Post-earthquake Analysis 6.6.2 MSS/TM/ETM+ Data: Urban Growth, Expert System Analysis References Part II Techniques and Applications Chapter 7: A Survey of the Evolution of Remote Sensing Imaging Systems and Urban Remote Sensing Applications 7.1 Introduction 7.2 Evolution of Remote Sensing Systems 7.2.1 Spatial Resolution 7.2.2 Radiometric Resolution 7.2.3 Spectral Resolution 7.2.4 Temporal Resolution 7.3 Evolution of Urban Remote Sensing and a Gallery of Applications 7.3.1 Early Urban Remote Sensing (1950–1970) 7.3.2 Recent Urban Remote Sensing (1971 to Present) 7.3.2.1 Land Cover and Land Use, Urban Structure, and Change Analyses 7.3.2.2 Urban Population Studies 7.3.2.3 Social Science Applications References Chapter 8: Classification of Urban Areas: Inferring Land Use from the Interpretation of Land Cover 8.1 Introduction 8.2 Urban Image Classification 8.2.1 Urban Land Use from Land Cover 8.2.2 Spectral Classifications 8.2.3 Spatial Classifications 8.3 Modified Maximum Likelihood Classification 8.4 Nearest Neighbor Spatial Pattern Recognition 8.5 Concluding Thoughts Regarding Classifications References Chapter 9: Processing Techniques for Hyperspectral Data 9.1 Introduction: Hyperspectral Data and Urban Remote Sensing 9.2 Pre-processing 9.2.1 Radiometric Correction 9.2.2 Geometric Correction 9.3 Spectral Libraries 9.4 Analysis Techniques 9.4.1 Data Optimization 9.4.2 Classification and Material Detection 9.4.3 Analysis Focusing on Mixed Pixels 9.5 Future Developments References Chapter 10: Segmentation and Object-Based Image Analysis 10.1 Introduction 10.2 Image Segmentation 10.2.1 Limitations of Pixel-Based Classification Techniques 10.2.2 Reasons for Object-Based Classification 10.2.3 Principles and Realization 10.3 Object-Based Classification 10.3.1 Object Features 10.3.2 Classification 10.3.3 Post Processing 10.3.4 Accuracy Assessment 10.4 Case Studies 10.4.1 Detecting Urban Features from IKONOS Data Using Methods of Object Oriented Image Analysis (Hofmann 2001) 10.4.2 Analysis of Urban Structure and Development. Applying Procedures for Automatic Mapping of Large-Area Data (De Kok References Chapter 11: Data Fusion in Remote Sensing of Urban and Suburban Areas 11.1 Introduction 11.2 Advanced Mathematical Tools for Data Fusion 11.2.1 Wavelet Transform (WT) 11.2.2 Multi-resolution Analysis (MRA) 11.3 Encrustation of Higher Spatial Resolution Quickbird Image in Low Resolution Image 11.3.1 Benefits of Encrustation 11.3.2 Methods 11.3.3 Illustration Example 11.4 The ARSIS Concept for Fusion of Images in Urban Areas 11.4.1 Introduction 11.4.2 Synthetic Merging Methods 11.4.3 Illustration Example 11.5 Fusion of Images, Databases and Punctual Measurements for Air Quality 11.5.1 Introduction 11.5.2 Methods 11.5.3 Illustrated Example References Chapter 12: Characterization and Monitoring of Urban/Peri-urban Ecological Function and Landscape Structure Using Satellite Dat 12.1 Introduction 12.1.1 Why Study Cities? 12.1.2 Remote Sensing and Urban Analysis 12.2 Analytical Methods and Techniques 12.2.1 Study Area 12.2.2 ASTER and MODIS Image Processing 12.2.3 Land Cover Classification of ASTER Data 12.2.4 Landscape Metric Calculation and Grid Construction 12.3 Results and Discussion References Chapter 13: Remote Sensing of Desert Cities in Developing Countries 13.1 Urban Areas in Desert Environment 13.1.1 Status and Extent of Desertification 13.1.2 Urban Areas in Africa 13.1.3 Urban Areas in West Asia 13.2 GIS and RS in Desert Cities 13.2.1 A General Framework for Mapping Desertification Hazards 13.2.2 Fusion of Optical and Radar Imagery 13.2.3 Surface Temperature Estimation 13.2.4 Green Belt Implementation 13.2.5 GIS Implementation at Municipalities 13.2.6 Other Urban Application Examples 13.3 Urban Areas Monitoring and Modeling 13.3.1 Land Use Change Detection 13.3.2 Land Use Change Analysis and Modeling 13.4 Case Studies 13.4.1 Adopted Methodology 13.4.2 The Case Study of Morocco 13.4.3 The Case Study of Saudi Arabia References Chapter 14: Remote Sensing of Urban Environmental Conditions 14.1 Introduction 14.2 Urban Physical Environment 14.2.1 Importance of Urban Vegetation 14.2.2 Urban Microclimates 14.2.3 Public Health Issues 14.3 Urban Vegetation Mapping 14.3.1 Normalized Difference Vegetation Index 14.3.2 Spectral Mixture Analysis 14.4 Urban Thermal Mapping 14.4.1 Principles of Thermal Radiation 14.4.2 Retrieval of Thermal Data from Satellite Imagery 14.4.3 Urban Heat Island 14.4.4 Relations Between Satellite Thermal Measurements and In Situ Air Temperatures Observations 14.5 Comparison of Environmental Conditions in New York City and Kuwait City References Chapter 15: Remote Sensing of Urban Land Use Change in Developing Countries: An Example from Büyükçekmece, Istanbul, Turkey 15.1 Introduction 15.2 Rural–Urban Land Use Changes 15.3 Urbanization in Developing Countries 15.4 Example: Analysis of Urban Growth in Istanbul, Turkey, Using Multitemporal Satellite Data 15.4.1 Study Area 15.4.2 Data and Methods 15.5 Results and Discussion 15.6 Conclusions References Chapter 16: Using Satellite Images in Policing Urban Environments 16.1 Introduction 16.2 Spatial Analysis of Crime 16.2.1 Data Versus Information in Community Policing 16.2.2 Crime Mapping 16.3 Application Examples 16.4 Dubai Police Practice1 16.4.1 Image Processing of IKONOS Data of Dubai 16.4.2 Crime Hotspot Analysis 16.4.3 Automated Vehicle Location (AVL) References Chapter 17: Using DMSP OLS Imagery to Characterize Urban Populations in Developed and Developing Countries 17.1 Introduction 17.2 Overview of the Nighttime Satellite Image Data Products 17.3 Summary of Several Applications of the Nighttime Imagery 17.4 Case Studies 17.4.1 Case Study#1 (Developed Country): Mapping Exurbia in the Conterminous United States 17.4.2 Case Study #2 (Developing Country): Exploring the Use of Nighttime Imagery in Guatemala References Remote Sensing of Urban and Suburban Areas provides instructors with a text reference that has a logical and easy-to-follow flow of topics around which they can structure the syllabi of their urban remote sensing courses. Topics have been chosen to bridge the gap between remote sensing and urban studies through a better understanding of the science that underlies both fields. In so doing, the book includes 19 chapters written by leading international experts in respected fields to provide a balanced coverage of fundamental issues in both remote sensing and urban studies. Emphasis are placed on