Multispectral Satellite Image Understanding

This book 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, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

Provides in-depth coverage of novel computer vision methods for remote sensing applications Includes end-of-chapter summaries and review questions With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center Includes supplementary material: sn.pub/extras

Klappentext

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:

• With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center
• Provides end-of-chapter summaries and review questions
• Presents a detailed review on remote sensing satellites
• Examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices
• Investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images
• Addresses the problem of detecting residential regions
• Describes a house and street network-detection subsystem
• Concludes with a summary of the key ideas covered in the bookThis 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 ofElectrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, Troy, NY, USA.

Inhalt
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.