Multispectral Satellite Image Understanding - From Land Classification to Building and Road Detection

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 CenterProvides end-of-chapter summaries and review questionsPresents a detailed review on remote sensing satellitesExamines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indicesInvestigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic imagesAddresses the problem of detecting residential regionsDescribes a house and street network-detection subsystemConcludes 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 of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, Troy, NY, USA.

Sommario

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.

Riassunto

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.

Testo aggiuntivo

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)

Relazione

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)

Dettagli sul prodotto

• Autori: Kim L Boyer, Kim L. Boyer, Cem UEnsalan, Cem Unsalan, Ce Ünsalan, Cem Ünsalan
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 20.06.2011
• EAN: 9780857296665
• ISBN: 978-0-85729-666-5
• Pagine: 186
• Peso: 434 g
• Illustrazioni: XVIII, 186 p.
• Serie: Advances in Computer Vision and Pattern Recognition; Advances in Computer Vision and Pattern Recognition; Advances in Pattern Recognition
• Categoria: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica