Introduction
Part I: Sensors
Remote Sensing Satellites and Airborne Sensors
Part II: The Multispectral Information
Linearized Vegetation Indices
Linearized Shadow and Water Indices
Part III: Land Use Classification
Review on Land Use Classification
Land Use Classification using Structural Features
Land Use Classification via Multispectral Information
Graph Theoretical Measures for Land Development
Part IV: Extracting Residential Regions
Feature Based Grouping to Detect Suburbia
Detecting Residential Regions by Graph Theoretical Measures
Part V: Building and Road Detection
Review on Building and Road Detection
House and Street Network Detection in Residential Regions
Part VI: Summarizing the Overall System
Final Comments
"synopsis" may belong to another edition of this title.
Rapid development of remote sensing technology in recent years has greatly increased availability of high-resolution satellite image data. However, detailed analysis of such large data sets also requires innovative new techniques in image and signal processing.
This important text/reference presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, making use of both well-known methods and cutting-edge techniques in computer vision, the book describes a system for the effective detection of single houses and streets in very high resolution.
Topics and features:
This pioneering work on automated satellite and aerial image-understanding systems will be of great interest to researchers in both remote sensing and computer vision, highlighting the benefit of interdisciplinary collaboration between the two communities. Urban planners and policy makers will also find considerable value in the proposed system.
Dr. Cem Ünsalan is an Associate Professor in the Department of Electrical and Electronics Engineering at Yeditepe University, Istanbul, Turkey. Dr. Kim Boyer is Professor and Head of the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, Troy, NY, USA.
From the reviews:
“The authors write that their aims were the proposal of a novel automated end-to-end system to analyze multispectral satellite images and to emphasize how many research problems in remote sensing applications are waiting to be solved by the computer vision community. Well, the book satisfies both these goals. ... it represents a good reference book, even a milestone, for teaching multispectral image understanding to students and/or young researchers.” (Primo Zingaretti, IAPR Newsletter, Vol. 34 (3), July-August, 2012)"About this title" may belong to another edition of this title.
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