"Digital Analysis of Remotely Sensed Imagery" by Jay Gao, Ph.D.

by George Maalouli

The Earth Science community has witnessed a continuous development in sensor technology since the launch of the first remote sensing satellite in the early 1970s. The emergence of a variety of systems capable of acquiring very high spatial and spectral resolutions, coupled with the latest trends in global positioning systems and the advances in computing technology, has been equally met by an expansion in the functionalities and sophistication of algorithms used in various Earth Science applications.

Most recent remote sensing publications tend to address a narrow audience with concentration on processing algorithms for either image-based or signal-based image data. On the other hand, in Digital Analysis of Remotely Sensed Imagery Dr. Gao attempts to address the entire process, from image acquisition, to spatial and spectral data processing and accuracy assessment, to data integration with existing technologies.

In easy-to-follow language, the first half of the book not only presents a review of the history, basic concepts, techniques, and algorithms used within the remote sensing discipline but expands into a host of application topics. The second half however progressively leans toward image processing algorithms and techniques with heavy doses of mathematical formulas that may be of interest only to researchers with formal remote sensing backgrounds.

Because of the continuing development in the various disciplines, it is not easy to address all current techniques and technologies, but the author has succeeded in covering most of today's systems and image analysis practices.

The book is organized into 14 chapters and may be classified into four themes. The first is a general historical perspective, the second deals with geometric processing and accuracy impact, while the third and largest addresses classification, image enhancement, and various image analysis techniques. The final theme touches on the basics of data integration with GPS and GIS systems.
Chapter one defines the basics of remote sensing. For the non-remote sensing specialist it will familiarize the reader with the basic technical terminology. For example, the commonly used term, digital number (DN) can be defined as the color of one pixel as recorded by the sensor. This chapter will also help in understanding the components and properties of remotely sensed data such as image enhancement, classification, and resolution.

In chapter two, the technical and operational properties and main area of application of existing satellites are reviewed from the early 1970s through mid-2008. This review includes meteorological, oceanographical, natural resources, radar, multispectral and hyperspectral, and high resolution sensors. A quick and general discussion is also given about analog image scanning. Again, this is a good general review that will be valuable to the non-remote sensing specialist.

Chapter three is a good reference for anyone who uses digital data. It summarizes the methods, media, and format of today's data storage. Some of the forms of data storage are well explained, such as BSQ, BIL, and BIP. Media storage such as CDs, DVDs, memory sticks, and hard disks are briefly discussed. Finally, sections related to image format and compression techniques are well presented.

Chapter four lists and summarizes many of the functionalities and capabilities of some of the existing remote sensing software packages including IDRISI, ERDAS Imagine, ENVI, ER Mapper, PCI, eCognition, and GRASS. The comparison between these systems provides the interested reader a decision-making tool for system selection and implementation.

Chapter five is devoted to geometric image processing. Still easy to follow by the non-remote sensing specialist, potential image distortions are well described with a very limited description of the UTM and NZMG projections and coordinate systems. The concepts and algorithms of various rectification methods are offered, starting with the simple affine transformation to the more complex rigorous sensor-specific and polynomials models. Some numerical results of rectification using specific imagery with specific models are shown, while the small section on image subsetting and mosaicking is very limited and generalized.

Chapters 6 through 13 will probably be more helpful to the remote sensing specialist. The presented information becomes more technical and leans more heavily toward image processing algorithms. The summary of each chapter and the general technical terms defined thereafter will, however, be a good source of information for the non-specialist. Chapter six is a good reference on image enhancement, and chapters 7 to 11 present in detail the various concepts of image analysis including spectral, neural, decision tree, spatial, and intelligent. Chapter 12 is a good reference for defining sources of inaccuracy during classification and methods for assessing and evaluating classification results. Chapter 13 describes a procedure for multi-temporal image analysis, change detection, and data presentation.

Finally in chapter 14, the author describes the concepts of GIS and GPS and makes a good argument for the necessity to integrate these concepts with the remote sensing discipline. Integration, models, and levels of integration are discussed with some supporting examples.
While this book best serves graduate and post-graduate students with strong remote sensing backgrounds, the depth of content and the comprehensive range of topics reaching beyond the normal remote sensing discipline make it a valuable and up-to-date reference work for practitioners of various disciplines such as surveyors, photogrammetrists, and Earth scientists.

George Maalouli is vice president and chief technical officer of the Seattle Division of Aero-Metric, Inc. He holds a M.Sc. in Aerial Surveying from the International Institute for Aerospace Survey and Earth Sciences in the Netherlands and has been actively involved in photogrammetry for 17 years.

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