This book provides the non-specialist with an introduction to quantitative evaluation of satellite and aircraft derived remotely retrieved data. Each chapter covers the pros and cons of digital remotely sensed data, without detailed mathematical treatment of computer based algorithms, but in a manner conductive to an understanding of their capabilities and limitations. Problems conclude each chapter. This third edition present the complete spectrum of acquisition, analysis and processing of remotely sensed data. The revisions reflect the developments in satellite and sensor programs as well as new processing techniques. A new chapter addresses hyperspectral image processing, and chapter twelve had been completely recast to focus it on data fusion.

Sources and characteristics of remote sensing image data -- Error correction and registration of image data -- The interpretation of digital image data -- Radiometric enhancement techniques -- Geometric enhancement using image domain techniques -- Multispectral transformations of image data -- Fourier transformation of image data -- Supervised classification techniques -- Clustering and unsupervised classification -- Feature reduction-- Image classification methodologies -- Data fusion -- Interpretation of hyperspectral image data -- Sattelite altitudes and periods -- Binary representation of decimal numbers -- Essential results from vector and matrix algebra -- Some fundamental material from probability and statistics -- Penalty function derivation of the maximum likelihood decision role.