488 pages | 16 Color Illus. | 174 B/W Illus.
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.
". . . well-organized and the chapters well-written . . . will serve as a comprehensive treatment for impervious surface remote sensing neophytes, as well as a valuable reference for veteran researchers and practitioners."
– Daniel L. Civco, Department of Natural Resources Management and Engineering, University of Connecticut, in Photogrammetric Engineering & Remote Sensing, July 2008, Vol. 74, No. 7
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