Titlebook: Remote Sensing Digital Image Analysis; An Introduction John A. Richards Book 19861st edition Springer-Verlag Berlin Heidelberg 1986 Analysi

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Supervised Classification Techniques, from those based upon probability distribution models for the classes of interest (such as outlined in Chap. 3) to those in which the multispectral space is partitioned into class-specific regions using optimally located surfaces. Irrespective of the particular method chosen, the essential practical steps are:

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Sources and Characteristics of Remote Sensing Image Data,ly the data is composed of discrete picture elements, or ., and radiometrically it is quantised into discrete brightness levels. Even data that is not recorded in digital form initially can be converted into discrete data by use of digitising equipment such as scanning microdensitometers.

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Error Correction and Registration of Image Data,s. The latter are referred to as radiometric errors and can result from the instrumentation used to record the data and from the effect of the atmosphere. Image geometry errors can arise in many ways. The relative motions of a satellite, its scanners and the earth, for example, can lead to errors of

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The Interpretation of Digital Image Data, two approaches that may be adopted in endeavouring to extract information. One involves the use of a computer to examine each pixel in the image individually with a view to making judgements about pixels specifically based upon their attributes. This is referred to as . since pixels with like attri

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