Remote Sensing Impervious Surfaces

Remote sensing of impervious surfaces has matured using advances in geospatial technology so recent that its applications have received only sporadic coverage in remote sensing literature. Remote Sensing of Impervious Surfaces is the first to focus entirely on this developing field. It provides detailed coverage of mapping, data extraction, and modeling techniques specific to analyzing impervious surfaces, such as roads and buildings. Written by renowned experts in the field, this book reviews the major approaches that apply to this emerging field as well as current challenges, developments, and trends. The authors introduce remote sensing digital image processing techniques for estimating and mapping impervious surfaces in urban and rural areas. Presenting the latest modeling tools and algorithms for data extraction and analysis, the book explains how to differentiate roads, roofs, and other manmade structures from remotely sensed images for individual analysis. The final chapters examine how to use impervious surface data for predicting the flow of storm- or floodwater and studying trends in population, land use, resource distribution, and other real-world applications in environmental, urban, and regional planning. Each chapter offers a consistent format including a concise review of basic concepts and methodologies, timely case studies, and guidance for solving problems and analyzing data using the techniques presented.

Introduction – Remote Sensing of Impervious Surfaces; Q. Weng PART I: DIGITAL REMOTE SENSING METHODS Estimating Percent Impervious Surfaces Using Multiple Regression; M. Bauer Sub-pixel Algorithms for Impervious Surface Mapping; C.S. Wu Mapping Impervious Surfaces Using Classification and Regression Tree Algorithm; G. Xian Mapping Urban Impervious Surfaces from Medium and High Spatial Resolution Multispectral Imagery; D. Lu and Q. Weng PART II: TECHNOLOGY ADVANCES IN IMPERVIOUS SURFACE MAPPING A SPLIT Model for Extraction of Subpixel Impervious Surface Information; Y.Q. Wang Use of Hyperspectral Imagery for Extracting Impervious Surface Data; Q. Weng and X. Hu Separation of Roads and Roofs Using Fractals; L.J. Quackenbush Fusion of Radar and Optical Data For Identification of Man-Made Structures; P. Gamba PART III: TRANSPORT-RELATED IMPERVIOUS SURFACES Extraction of Transportation Infrastructure From Hyperspectral Data; R. Sugumaran Road Extraction From SAR Imagery; U. Stilla Road Networks Derived From High Spatial Resolution Satellite Remote Sensing Data; R. Peteri Spectral Characteristics of Asphalt Roads; M. Herold PART IV: ROOF-RELATED IMPERVIOUS SURFACES Urban 3D Building Model From LIDAR Data and Aerial Images; G. Zhou Building Extraction From Aerial Imagery; A. Gruen SAR Images of Built-Up Areas: Models and Data Elaborations; G. Franceschetti Multi-scale Roof Mapping Using Fused Multi-Resolution Optical Satellite Images; Y. Zhang PART V: IMPERVIOUS SURFACE DATA APPLICATIONS Impervious Surface Area and Its Effect On Water Quality and Water Abundance; T. Carlson Impervious Surface Data for Hydrological Modeling of Water Flow; A.M. Melesse The Growth of Impervious Surface Coverage and Aquatic Fauna; R.R. Gillies Using Remotely Sensed Impervious Surface Data to Estimate Population; B. Liang, Q. Weng, and D. Lu