"Jay Gao's book on the analysis of remote sensing imagery is a
well-written, easy-to-read, and informative text best serving
graduate students in geosciences, and practitioners in the field of
digital image analysis. Although Dr. Gao states that he has
targeted his book at upper-level undergraduates and lower-level
postgraduate students, its rigor and depth of mathematical analysis
would challenge most students without prior experience in remote
sensing and college-level mathematics. The book covers a lot of
ground quickly, beginning with a basic explanation of pixels,
digital numbers and histograms and advancing rapidly through a
description of the most well-known satellite systems to data
storage formats, rectification and classification. It best serves
students who have already taken an introductory course in remote
sensing. Following a three-chapter description of the basics the
remaining eleven chapters are dedicated to the description of the
most common image processing systems and the details of the image
analysis functions which can be carried out. The largest portion of
the text covers classification - spectral and spatial, neural
networks, decision trees and expert systems - and is an invaluable
reference to anyone interested in understanding image analysis
terminology and the algorithms behind these different systems. The
last chapter of the text is addressed to practitioners wishing to
integrate remote sensing image data with GIS and/or GPS data. The
text is nicely structured so that individual chapters can easily be
skipped when their content is not of interest to the reader without
impairing the understanding of later chapters.
"The first three chapters of the book cover introductory
material that the reader should be familiar with for the most part,
but also includes a very handy summary of today's satellite
systems. Chapter one addresses basic material, such as pixel DN,
coordinates, feature space, histograms, and spatial, spectral,
temporal and radiometric resolution normally covered in an
introductory course in remote sensing. Chapter two presents a very
informative and up-to-date overview of today's satellite
instruments including meteorological, oceanographic, earth
resources, hyperspectral and radar instruments. Instrument and
orbital parameters are presented in tabular form and make it easy
to look up technical details such as spectral and spatial
resolution, orbit type, repeat cycle and other instrument
characteristics quickly. Written explanations are clear, readable
and provide lots of interesting insight and useful tidbits of
information such as potential problems and the cost of imagery. For
technicians and programmers the third chapter provides details on
storage formats, including descriptions of BSQ, BIL and BIP binary
formats, and the most common graphics formats like GIF, TIFF and
JPEG together with data compression techniques. Non-technicians can
skip this chapter since image processing software will generally
take care of format conversions internally without a need for
understanding the nuances of each.
"Chapters four will be of interest to anyone considering the
purchase of image processing software, or trying to understand the
differences between systems. Gao provides a useful overview of
existing software - IDRISI, ERDAS Imagine, ENVI, ER Mapper, PCI,
eCognition and GRASS. A brief history of each provides useful
background, and a discussion of the features of each together with
a comparison (also given in tabular form) is informative to anyone
considering a purchase.
"Chapter five can also be viewed as a stand-alone reference on
rectification, but also serves as an excellent overview of the
problems of dealing with mapping on a curved surface and has
particular application for geographers and cartographers. It
discusses the sources of geometric distortion, coordinated systems
and projections, how image rectification is done - including the
use of ground control points and implications for the order of
transformation employed. There is a nice example showing how
accuracy is influenced by the number of GCPs employed for SPOT and
Landsat TM. For non-technical students the transformation
mathematics can be skipped. A rather minimal section on image
subsetting and mosaicking is included. Chapter six continues in
much the same vein as the previous chapter, but discussing image
enhancement - techniques that improve the visual quality of an
image. The terms introduced here, such as density slicing, linear
enhancement, stretching, and histogram equalization, will be
familiar to users of image processing software and Gao provides a
useful explanation of each in turn. Other application-oriented
utilities such as band ratioing, vegetation indices, IHS and
Tasseled Cap transformations and principal component analysis are
presented in a form which is understandable to students with good
mathematical grounding.
"The remainder of the text deals, to a large extent, with the
topic of classification. Chapter seven initially discusses elements
of image interpretation, but then devotes the chapter to a detailed
presentation of the most common (and affordable) of these -
spectral analysis. Gao presents the different algorithms used to
define spectral distance, and then devotes text to a discussion of
the inner workings of unsupervised classification systems. The
section on supervised classification is a very useful reference for
anyone undertaking this process - describing how to set about the
classification process, the differences between the different
classifiers, and how to choose an appropriate one. The concepts of
fuzzy logic and sub-pixels classifiers are also presented
briefly.
"From this point on, the text becomes much more specialized and
technical and is geared towards graduate students, those carrying
out research projects, and those interested in algorithmic detail.
Chapter 8 is the first dealing with artificial intelligence and
describes th
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