Over the last fifty years, humanity has developed an extraordinary shared utility: the Global Positioning System. Even as it guides us across town, GPS helps land planes, route mobile calls, anticipate earthquakes, predict weather, locate oil deposits, measure neutrinos, grow our food, and regulate global finance. It is as ubiquitous and essential as another Cold War technology, the Internet. In Pinpoint, Greg Milner takes us on a fascinating tour of a hidden system that touches almost every aspect of our modern life.
While GPS has brought us breathtakingly accurate information about our planetary environment and physical space, it has also created new forms of human behavior. We have let it saturate the world’s systems so completely and so quickly that we are just beginning to confront the possible consequences. A single GPS timing flaw, whether accidental or malicious, could bring down the electrical grid, hijack drones, or halt the world financial system. The use, and potential misuse, of GPS data by government and corporations raise disturbing questions about ethics and privacy. GPS may be altering the nature of human cognition—possibly even rearranging the gray matter in our heads.
Pinpoint tells the sweeping story of GPS from its conceptual origins as a bomb guidance system to its presence in almost everything we do. Milner examines the different ways humans have understood physical space, delves into the neuroscience of cognitive maps, and questions GPS’s double-edged effect on our culture. A fascinating and original story of the scientific urge toward precision, Pinpoint offers startling insight into how humans understand their place in the world.
As mobile computing devices become more and more prevalent and powerful, they are becoming more and more useful in the field of law enforcement investigations and forensics. Of all the widely used mobile applications, none have more potential for helping solve crimes than those with geo-location tools.
Written for investigators and forensic practitioners, Google Earth Forensics is written by an investigator and trainer with more than 13 years of experience in law enforcement who will show you how to use this valuable tool anywhere at the crime scene, in the lab, or in the courtroom.Learn how to extract location-based evidence using the Google Earth program or app on computers and mobile devicesCovers the basics of GPS systems, the usage of Google Earth, and helps sort through data imported from external evidence sourcesIncludes tips on presenting evidence in compelling, easy-to-understand formats
The book shows you how satellite, inertial, and other navigation technologies work, and focuses on processing chains and error sources. In addition, you get a clear introduction to coordinate frames, multi-frame kinematics, Earth models, gravity, Kalman filtering, and nonlinear filtering. Providing solutions to common integration problems, the book describes and compares different integration architectures, and explains how to model different error sources. You get a broad and penetrating overview of current technology and are brought up to speed with the latest developments in the field, including context-dependent and cooperative positioning.
See What’s New in the Fourth Edition:
Up-to-date information on GNSS and GPS modernization Changes in hardware, software, and procedures Comprehensive treatment of novel signals on new blocks of satellites (L5 and L2C)
The book minimizes your reliance on mathematical explanations and maximizes use of illustrations and examples that allow you to visualize and grasp key concepts. The author explains the progression of ideas at the foundation of satellite positioning and delves into some of the particulars. He keeps presentation practical, providing a guide to techniques used in GPS, from their design through observation, processings, real-time kinematic (RTK), and real-time networks. These features and more make it easier for you to meet the challenge of keeping up in this field.
The book introduces object-oriented modeling including key concepts such as abstraction, inheritance and encapsulation. It shows how these ideas can be used to model, process and visualize geographic information leading the reader from initial ideas of class design through to the implementation of feature rich raster and vector models of space. It includes some of the more recent developments in internet technologies such as web-based applets, remote communication and XML, showing how these can be used to deliver geographic information in a modern computing environment.
The text is aimed at new programmers as well as those in fields such as geography, GIS, remote sensing, archaeology and biology who wish to make use of geographic information. It provides a useful course text for advanced undergraduates and postgraduates in these fields. The material is heavily example-led, and contains programming exercises and quizzes, making it suitable for self-paced learning.
Using Python code throughout, Xiao breaks the subject down into three fundamental areas:
Geometric Algorithms Spatial Indexing Spatial Analysis and Modelling With its comprehensive coverage of the many algorithms involved, GIS Algorithms is a key new textbook in this complex and critical area of geography.
Plant Image Analysis: Fundamentals and Applicationsintroduces the basic concepts of image analysis and discusses various techniques in plant imaging, their applications, and future potential. Several types of imaging techniques are discussed including RGB, hyperspectral, thermal, PRI, chlorophyll fluorescence, ROS, and chromosome imaging. The book also covers the use of these techniques in assessing plant growth, early detection of disease and stress, fruit crop yield, plant chromosome analysis, plant phenotyping, and nutrient status both in vivo and in vitro.
The book is an authoritative guide for researchers and those teaching in the fields of stress physiology, precision agriculture, agricultural biotechnology, and cell and developmental biology. Graduate students and professionals using machine vision in plant science will also benefit from this comprehensive resource.
Using a hands-on approach grounded in relevant GIS and disaster management theory and practice, this textbook provides coverage of the basics of GIS. It examines what GIS can and can’t do, GIS data formats (vector, raster, imagery), and basic GIS functions, including analysis, map production/cartography, and data modeling. It presents a series of real-life case studies that illustrate the GIS concepts discussed in each chapter. These case studies supply readers with an understanding of the applicability of GIS to the full disaster management cycle.
Providing equal treatment to each disaster management cycle phase, the book supplies disaster management practitioners and students with coverage of the latest developments in GIS for disaster management and emerging trends. It takes a learning-by-examples approach to help readers apply what they have learned from the examples and disaster management scenarios to their specific situations.
The book illustrates how GIS technology can help disaster management professionals, public policy makers, and decision-makers at the town, county, state, federal, and international levels. Offering software-neutral best practices, this book is suitable for use in undergraduate- or graduate-level disaster management courses. Offering extensive career advice on GIS for disaster management from working professionals, the book also includes a GIS for disaster management research agenda and ideas for staying current in the field.
A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods
Noel Cressie and Christopher K. Wikle, are also winners of the 2011 PROSE Award in the Mathematics category, for the book “Statistics for Spatio-Temporal Data” (2011), published by John Wiley and Sons. (The PROSE awards, for Professional and Scholarly Excellence, are given by the Association of American Publishers, the national trade association of the US book publishing industry.)
Statistics for Spatio-Temporal Data has now been reprinted with small corrections to the text and the bibliography. The overall content and pagination of the new printing remains the same; the difference comes in the form of corrections to typographical errors, editing of incomplete and missing references, and some updated spatio-temporal interpretations.
From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models.
Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes.
Topics of coverage include:Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data
Throughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material. Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.
This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control.
Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
See What’s New in the Second Edition:
Summaries at the end of each chapter Worked examples of techniques described Additional material on matrices and vectors Further material on map projections New material on spatial correlation A new section on global positioning systems
Written for those who need to make use geographic information systems but have a limited mathematical background, this book introduces the basic statistical techniques commonly used in geographic information systems and explains best-fit solutions and the mathematics behind satellite positioning. By understanding the mathematics behind the gathering, processing, and display of information, you can better advise others on the integrity of results, the quality of the information, and the safety of using it.
Professionals in fields ranging from geology, geography and geoinformatics to physics, transportation, and law enforcement will benefit from this comprehensive discussion of topographic LiDAR principles, systems, data acquisition, and data processing techniques. The book covers ranging and scanning fundamentals, and broad, contemporary analysis of airborne LiDAR systems, as well as those situated on land and in space. The authors present data collection at the signal level in terms of waveforms and their properties; at the system level with regard to calibration and georeferencing; and at the data level to discuss error budget, quality control, and data organization. They devote the bulk of the book to LiDAR data processing and information extraction and elaborate on recent developments in building extraction and reconstruction, highlighting quality and performance evaluations. There is also extensive discussion of the state-of-the-art technological developments used in: filtering algorithms for digital terrain model generation; strip adjustment of data for registration; co-registration of LiDAR data with imagery; forestry inventory; and surveying.
Readers get insight into why LiDAR is the effective tool of choice to collect massive volumes of explicit 3-D data with unprecedented accuracy and simplicity. Compiled by leading experts talking about much of their own pioneering work, this book will give researchers, professionals, and senior students novel ideas to supplement their own experience and practices.
Using Python code throughout, Xiao breaks the subject down into three fundamental areas:
Geometric Algorithms Spatial Indexing Spatial Analysis and Modelling With its comprehensive coverage of the many algorithms involved, GIS Algorithms is a key new textbook in this complex and critical area of geography.
The book begins with an introduction to the basic processes that ensure the acquisition of space-borne imagery and provides an overview of the main satellite observation systems. It then describes visual and digital image analysis, highlights various interpretation techniques, and outlines their applications to science and management. The latter part of the book covers the integration of remote sensing with GIS for environmental analysis.
Based on the first English version published in 2010, this latest edition has been written to reflect a global audience, and factors in international debates and legal issues surrounding EO, as well as future developments and trends.
New in the Second Edition:
Includes additional illustrations now in full color Uses sample images acquired from different ecosystems at different spatial resolutions to illustrate different interpretation techniques Updates information on recent satellite missions (Landsat-8, Sentinel-2, hyperspectral and hyperspatial programs) Covers near-ground missions (including UAV) and ground sensors (spectro-radiometers, cameras, LIDAR, etc.) to support EO analysis Offers analysis of image spatial properties Presents material on visual analysis, time series analysis, and data fusion Provides examples of EO data that cover different environmental problems, with particular relevance to global observation
Fundamentals of Satellite Remote Sensing: An Environmental Approach, Second Edition details the tools that provide global, recurrent, and comprehensive views of the processes affecting the Earth and is a must-have for researchers, academics, students, and professionals involved in the field of environmental science.
Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted logit model (GTWLM), spatio-temporal panel logit model (ST-PLM) and generalized spatio-temporal logit model (GSTLM), are proposed. GTWLM, which considers spatio-temporal non-stationarity, includes temporal data in a spatio-temporal framework by proposing a spatio-temporal distance. ST-PLM incorporates the spatio-temporal correlation and individual effect in one model. By integrating GTWLM and ST-PLM, the GSTLM explores spatio-temporal non-stationarity and correlations simultaneously, whilst considering their individual effects to construct an integrated model.
Secondly, a MOO-based two-level spatial planning of land use is proposed. The spatial planning aims at managing and coordinating the land use at different geographic extents and involves spatial layouts and structures of land use at different levels. In spatial planning, GIS and Remote Sensing are used to evaluate, analyze, and measure environmental, economic and social issues. The quantitative relationships between these objectives and spatial land use allocation are then used as rules in the MOO process to simulate environmental conditions under different spatial land use allocation scenarios. The book features a case study of Shenzhen city, the most important Special Economic Zone in China.
This book will be of interest to academics and professionals in the fields of urban planning, land resource management, remote sensing and geographic information systems.
New and Updated in the Second Edition:
Web-based image viewing with Google Earth Aerial platforms Existing digital photogrammetric software systems, including Intergraph image station, Autodesk, and Oracle Spatial Land management and cadaster Imaging sensors such as laser scanning, image spectrometry, radar imaging, and radar interferometry
With the advent of high-resolution satellite systems in stereo, the theory of analytical photogrammetry restituting 2D image information into 3D is of increasing importance, merging the remote sensing approach with that of photogrammetry. This text describes the fundamentals of these approaches in detail, with an emphasis on global, regional, and local applications. It provides a short introduction to the GPS satellite positioning system in the context of data integration.
An extensive overview of the basic elements of GIS technologies and data management approaches, as well as the widely employed positioning systems such as GPS and GSM networks, complete the presentation of the technological framework for geoinformation. Appropriate for GIS courses at all levels, the book proceeds beyond the science and technology to tackle cost considerations and practical implementation issues, giving you a starting point for multidisciplinary new activities and services in the future.
* Contains recent UV applications not previously available in book form such as ozone, auroral images, and ionospheric sensing
* Features broad coverage of fundamentals of atmospheric geophysics with values for fluxes, cross-sections, and radiances
* Covers techniques that illustrate principles of measurements with typical values
* Contains numerous references to original literature
Hyperspectral Remote Sensing of Vegetation integrates this knowledge, guiding readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Taking a practical approach to a complex subject, the book demonstrates the experience, utility, methods and models used in studying vegetation using hyperspectral data. Written by leading experts, including pioneers in the field, each chapter presents specific applications, reviews existing state-of-the-art knowledge, highlights the advances made, and provides guidance for the appropriate use of hyperspectral data in the study of vegetation as well as its numerous applications, such as crop yield modeling, crop and vegetation biophysical and biochemical property characterization, and crop moisture assessment.
This comprehensive book brings together the best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, vegetation classification, biophysical and biochemical modeling, crop productivity and water productivity mapping, and modeling. It provides the pertinent facts, synthesizing findings so that readers can get the correct picture on issues such as the best wavebands for their practical applications, methods of analysis using whole spectra, hyperspectral vegetation indices targeted to study specific biophysical and biochemical quantities, and methods for detecting parameters such as crop moisture variability, chlorophyll content, and stress levels. A collective "knowledge bank," it guides professionals to adopt the best practices for their own work.
The text stresses basic concepts and principles of practice involved in urban planning as most widely practiced, particularly in small and medium-sized communities. It introduces engineering students to land-use planning as a foundation for infrastructure systems planning and development. It also presents plan implementation devices such as zoning, land subdivision control, official mapping, and capital improvement programming. It describes the factors affecting good land subdivision design and improvement. In addition, the text illustrates the importance of good mapping and control surveys for planning purposes. Written from the perspective that cities are social and economic as well as physical entities, the book offers a historical context for urban planning.
There are a large number of texts on the subject of urban planning, but most generally do not address in any comprehensive way the engineering problems encountered in urban planning. This book delineates these problems and stresses the importance of close cooperation between civil engineers and planning professionals to achieving effective urban planning. Armed with this information, students can become more knowledgeable participants in the urban planning process and more effective members of urban planning teams and governmental and consulting agency staff.
Her presentation of these maps reclaims, repurposes, and discovers new and even inadvertent uses for them, including documentary, memorial, preservation, interpretation, political, or simply aesthetic. GPS has been available to both civilians and the military since 1991; the World Wide Web democratized the distribution of data in 1992; Google Earth has captured global bird’s-eye views since 2005. Technology has brought about a revolutionary shift in our ability to navigate, inhabit, and define the spatial realm. The traces of interactions, both physical and virtual, charted by the maps in Close Up at a Distance define this shift.
Significantly updated and expanded, this reader-friendly manual introduces the fundamentals in mathematics and physics needed to perform area-wide mapping, inventory, data conversion, and analysis. The text maintains a focus on the practical aspects of these technologies and remains the only resource to cover the areas of GIS, GPS, and remote sensing with such breadth and clarity. An expanded index, new and revised figures, a color insert, and an easier to read format are among the many improvements to this edition.
New to the Second Edition:
Revised chapters reflecting the changes that have occurred in the technology, applications, and usage of geospacial science Coverage of GIS applications in automobile navigation and enterprise-wide applications A new chapter devoted to basic statistics and least squares solutions Expanded international scope that addresses the other Global Navigation Satellite Systems (GNSS), including the Russian Federation system (GLONASS), the Chinese system (COMPASS), and the European space agency system (GALILEO) A new chapter covering Light Detection and Ranging (LiDAR) A new chapter that addresses privacy issues, legal concerns, and the emerging field of public participation GIS (PPGIS) New material on the expanding field of geovisualization
The text presents many real-world applications, including road map navigation using GPS, as well as problems associated with mapping, inventory of land parcels, and data analysis. Complete with helpful references, decision making tools, and many new case studies, this time-saving resource provides the practical understanding required to harness the potential of these dynamic technologies.
The book covers all of the components needed to develop an LBIS. It discusses cellular phone programming using the Java ME platform, positioning technologies, databases and spatial databases, communications, client- and server-side data processing, and real-time data visualization via Google Maps and Google Earth. Using freely available software, the authors include many code examples and detailed instructions for building your own system and setting up your entire development environment.
A companion website at www.csee.usf.edu/~labrador/LBIS provides additional information and supporting material. It contains all of the software packages and applications used in the text as well as PowerPoint slides and laboratory examples.
Although LBIS applications are still in the beginning stages, they have the potential to transform our daily lives, from warning us about possible health problems to monitoring pollution levels around us. Exploring this novel technology, Location-Based Information Systems describes the technical components needed to create location-based services with an emphasis on nonproprietary, freely available solutions that work across different technologies and platforms.
See What’s New in the Second Edition:
All project instructions are in ArcGIS 10.2 using geodatabase datasets New chapters on regionalization methods and Monte Carlo simulation Popular tasks automated as a convenient toolkit: Huff Model, 2SFCA accessibility measure, regionalization, Garin-Lowry model, and Monte Carlo based spatial simulation Advanced tasks now implemented in user-friendly programs or ArcGIS: centrality indices, wasteful commuting measure, p-median problem, and traffic simulation
Each chapter has one subject theme and introduces the method (or a group of related methods) most relevant to the theme. While each method is illustrated in a special case of application, it can also be used to analyze different issues. For example, spatial regression is used to examine the relationship between job access and homicide patterns; systems of linear equations are analyzed to predict urban land use patterns; linear programming is introduced to solve the problem of wasteful commuting and allocate healthcare facilities; and Monte Carlo technique is illustrated in simulating urban traffic.
The book illustrates the range of computational methods and covers common tasks and major issues encountered in a spatial environment. It provides a platform for learning technical skills and quantitative methods in the context of addressing real-world problems, giving you instant access to the tools to resolve major socio-economic issues.
Time-Of-Flight (TOF) Range-Imaging (TOF) is an emerging sensor technology able to deliver, at the same time, depth and intensity maps of the scene under observation. Featuring different sensor resolutions, RIM cameras serve a wide community with a lot of applications like monitoring, architecture, life sciences, robotics, etc. This book will bring together experts from the sensor and metrology side in order to collect the state-of-art researchers in these fields working with RIM cameras. All the aspects in the acquisition and processing chain will be addressed, from recent updates concerning the photo-detectors, to the analysis of the calibration techniques, giving also a perspective onto new applications domains.
Dr. Schowengerdt presents an advanced unified framework and rationale that uniquely empowers the reader with the latest critical thinking skills and prerequisite knowledge needed to successfully design, develop and incorporate maintainable remote sensing solutions for real-world application. Advanced remote sensing image processing techniques such as hyperspectral image analysis, fusion of multisensor images and digital elevation model extraction from stereo imagery are discussed theoretically in terms of spectral, spatial, and geometric models. An expanded exercise section is also included at the end of each chapter allowing for the greatest level of mastery ever.Features a new lively discussion of the NASA EOS satellites, Terra and Aqua, and the commercial satellites IKONOS and QuickbirdNew larger format provides additional access to 32 PAGE - FULL COLOR plate insert and improved readabilityAdditional data processing algorithms help connect and enhance the collective understanding of engineering design and remotely sensed data
What’s new in the Second Edition:
Additional material on geographically-weighted statistics and local regression approaches A better overview of local models with reference to recent critical reviews about the subject area Expanded coverage of individual methods and connections between them Chapters have been restructured to clarify the distinction between global and local methods A new section in each chapter references key studies or other accounts that support the book Selected resources provided online to support learning
An introduction to the methods and their underlying concepts, the book uses worked examples and case studies to demonstrate how the algorithms work their practical utility and range of application. It provides an overview of a range of different approaches that have been developed and employed within Geographical Information Science (GIScience). Starting with first principles, the author introduces users of GISystems to the principles and application of some widely used local models for the analysis of spatial data, including methods being developed and employed in geography and cognate disciplines. He discusses the relevant software packages that can aid their implementation and provides a summary list in Appendix A.
Presenting examples from a variety of disciplines, the book demonstrates the importance of local models for all who make use of spatial data. Taking a problem driven approach, it provides extensive guidance on the selection and application of local models.
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.
This book describes all components of a digital airborne camera from the object to be imaged to the mass memory device. So the image quality influencing processes in nature are described, as for instance the reflection of the electromagnetic sun spectrum at the objects to be imaged and the influence of the atmosphere. Also, the essential features of the new digital sensor system, their characteristics and parameters, are addressed and put into the system context. The complexity of the cooperation of all camera components, as for instance optics, filters, detector elements, analogue and digital electronics, software and so forth, becomes transparent. The book includes also the description of example systems.
The manual covers the fundamentals of each of these topical areas, providing the requisite mathematics, computer science and physics necessary to understand how the technologies work, assuming some elementary background in calculus and physics. It also shows how the technologies can be used together and focuses on their commonalities. A number of applications such as mapping and environmental modeling are presented, and a website accompanies the book.
Each chapter describes the nature of a problem, examines the purpose and scope of a GIS application, presents the methods used to develop the application, and then goes on to provide results and offer a conclusion as well as supporting information. When appropriate, the chapters present the underlying statistical approach for the GIS software that is used. Applicable data sets and color maps produced by use of GIS are included for download at the CRC webiste.
Concentrating more on the approach and less on the specific software, the authors describe the methods used to develop an application and discuss limitations to the algorithms and the programming code used. They then summarize the application in terms of what it does, how it works, its limitations, and its potential uses. The book provides a toolkit for the acquisition, management, and analysis of spatial data throughout the agriculture value chain.
Much of the basic `workings' of synthetic aperture radars is rooted in the concepts of signal processing. Starting with that premise, this book explores in depth the fundamental principles upon which the spotlight mode of SAR imaging is constructed, using almost exclusively the language, concepts, and major building blocks of signal processing.
Spotlight-Mode Synthetic Aperture Radar: A Signal Processing Approach is intended for a variety of audiences. Engineers and scientists working in the field of remote sensing but who do not have experience with SAR imaging will find an easy entrance into what can seem at times a very complicated subject. Experienced radar engineers will find that the book describes several modern areas of SAR processing that they might not have explored previously, e.g. interferometric SAR for change detection and terrain elevation mapping, or modern non-parametric approaches to SAR autofocus. Senior undergraduates (primarily in electrical engineering) who have had courses in digital signal and image processing, but who have had no exposure to SAR could find the book useful in a one-semester course as a reference.