Techniques and Methods in Urban Remote Sensing

The second edition of  Urban Remote Sensing  is a state-of-the-art review of the latest progress in the subject. The text examines how evolving innovations in remote sensing allow to deliver the critical information on cities in a timely and cost-effective way to support various urban management activities and the scientific research on urban morphology, socio-environmental dynamics, and sustainability.  Chapters are written by leading scholars from a variety of disciplines including remote sensing, GIS, geography, urban planning, environmental science, and sustainability science, with case studies predominately drawn from North America and Europe.  A review of the essential and emerging research areas in urban remote sensing including sensors, techniques, and applications, especially some critical issues that are shifting the directions in urban remote sensing research. Illustrated in full color throughout, including numerous relevant case studies and extensive discussions of important concepts and cutting-edge technologies to enable clearer understanding for non-technical audiences.  Urban Remote Sensing, Second Edition  will be of particular interest to upper-division undergraduate and graduate students, researchers and professionals working in the fields of remote sensing, geospatial information, and urban & environmental planning.

Urban Remote Sensing is designed for upper level undergraduates, graduates, researchers and practitioners, and has a clear focus on the development of remote sensing technology for monitoring, synthesis and modeling in the urban environment. It covers four major areas: the use of high-resolution satellite imagery or alternative sources of image date (such as high-resolution SAR and LIDAR) for urban feature extraction; the development of improved image processing algorithms and techniques for deriving accurate and consistent information on urban attributes from remote sensor data; the development of analytical techniques and methods for deriving indicators of socioeconomic and environmental conditions that prevail within urban landscape; and the development of remote sensing and spatial analytical techniques for urban growth simulation and predictive modeling.

Urban Remote Sensing is designed for upper level undergraduates, graduates, researchers and practitioners, and has a clear focus on the development of remote sensing technology for monitoring, synthesis and modeling in the urban environment. It covers four major areas: the use of high-resolution satellite imagery or alternative sources of image date (such as high-resolution SAR and LIDAR) for urban feature extraction; the development of improved image processing algorithms and techniques for deriving accurate and consistent information on urban attributes from remote sensor data; the development of analytical techniques and methods for deriving indicators of socioeconomic and environmental conditions that prevail within urban landscape; and the development of remote sensing and spatial analytical techniques for urban growth simulation and predictive modeling.

Discover cutting edge theory and applications of modern remote sensing in geology, oceanography, atmospheric science, ionospheric studies, and more    The thoroughly revised third edition of the  Introduction to the Physics and Techniques of Remote Sensing  delivers a comprehensive update to the authoritative textbook, offering readers new sections on radar interferometry, radar stereo, and planetary radar. It explores new techniques in imaging spectroscopy and large optics used in Earth orbiting, planetary, and astrophysics missions. It also describes remote sensing instruments on, as well as data acquired with, the most recent Earth and space missions.  Readers will benefit from the brand new and up-to-date concept examples and full-color photography, 50% of which is new to the series. You’ll learn about the basic physics of wave/matter interactions, techniques of remote sensing across the electromagnetic spectrum (from ultraviolet to microwave), and the concepts behind the remote sensing techniques used today and those planned for the future.  The book also discusses the applications of remote sensing for a wide variety of earth and planetary atmosphere and surface sciences, like geology, oceanography, resource observation, atmospheric sciences, and ionospheric studies. This new edition also incorporates:  A fulsome introduction to the nature and properties of electromagnetic waves An exploration of sensing solid surfaces in the visible and near infrared spectrums, as well as thermal infrared, microwave, and radio frequencies A treatment of ocean surface sensing, including ocean surface imaging and the mapping of ocean topography A discussion of the basic principles of atmospheric sensing and radiative transfer, including the radiative transfer equation Perfect for senior undergraduate and graduate students in the field of remote sensing instrument development, data analysis, and data utilization,  Introduction to the Physics and Techniques of Remote Sensing  will also earn a place in the libraries of students, faculty, researchers, engineers, and practitioners in fields like aerospace, electrical engineering, and astronomy.

Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.

Provides up-to-date developments in the field of remote sensing by assessing scale issues in land surface, properties, patterns, and processes Scale is a fundamental and crucial issue in remote sensing studies and image analysis. GIS and remote sensing scientists use various scaling techniques depending on the types of remotely sensed images and geospatial data used. Scaling techniques affect image analysis such as object identification and change detection. This book offers up-to-date developments, methods, and techniques in the field of GIS and remote sensing and features articles from internationally renowned authorities on three interrelated perspectives of scaling issues: scale in land surface properties, land surface patterns, and land surface processes. It also visits and reexamines the fundamental theories of scale and scaling by well-known experts who have done substantial research on the topics. Edited by a prominent authority in the geographic information science community, Scale Issues in Remote Sensing: Offers an extensive examination of the fundamental theories of scale issues along with current scaling techniques Studies scale issues from three interrelated perspectives: land surface properties, patterns, and processes Addresses the impact of new frontiers in Earth observation technology (high-resolution, hyperspectral, Lidar sensing, and their synergy with existing technologies) and advances in remote sensing imaging science (object-oriented image analysis and data fusion) Prospects emerging and future trends in remote sensing and their relationship with scale Scale Issues in Remote Sensing is ideal as a professional reference for practicing geographic information scientists and remote sensing engineers as well as supplemental reading for graduate level students.

Remote Sensing plays a key role in monitoring the various manifestations of global climate change. It is used routinely in the assessment and mapping of biodiversity over large areas, in the monitoring of changes to the physical environment, in assessing threats to various components of natural systems, and in the identification of priority areas for conservation. This book presents the fundamentals of remote sensing technology, but rather than containing lengthy explanations of sensor specifications and operation, it concentrates instead on the application of the technology to key environmental systems. Each system forms the basis of a separate chapter, and each is illustrated by real world case studies and examples. Readership The book is intended for advanced undergraduate and graduate students in earth science, environmental science, or physical geography taking a course in environmental remote sensing. It will also be an invaluable reference for environmental scientists and managers who require an overview of the use of remote sensing in monitoring and mapping environmental change at regional and global scales. Additional resources for this book can be found at: http://www.wiley.com/go/purkis/remote.

Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’?tudes Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.

Following the successful publication of the 1st edition in 2009, the 2nd edition maintains its aim to provide an application-driven package of essential techniques in image processing and GIS, together with case studies for demonstration and guidance in remote sensing applications. The book therefore has a “3 in 1” structure which pinpoints the intersection between these three individual disciplines and successfully draws them together in a balanced and comprehensive manner. The book conveys in-depth knowledge of image processing and GIS techniques in an accessible and comprehensive manner, with clear explanations and conceptual illustrations used throughout to enhance student learning. The understanding of key concepts is always emphasised with minimal assumption of prior mathematical experience. The book is heavily based on the authors’ own research. Many of the author-designed image processing techniques are popular around the world. For instance, the SFIM technique has long been adopted by ASTRIUM for mass-production of their standard “Pan-sharpen” imagery data. The new edition also includes a completely new chapter on subpixel technology and new case studies, based on their recent research.