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Remote Sensing Digital Image Analysis 6Ed (Hb 2022) at Meripustak

Remote Sensing Digital Image Analysis 6Ed (Hb 2022) by RICHARDS J.A., SPRINGER

Books from same Author: RICHARDS J.A.

Books from same Publisher: SPRINGER

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  • General Information  
    Author(s)RICHARDS J.A.
    PublisherSPRINGER
    ISBN9783030823269
    Pages567
    BindingHardbound
    LanguageEnglish
    Publish YearJanuary 2022

    Description

    SPRINGER Remote Sensing Digital Image Analysis 6Ed (Hb 2022) by RICHARDS J.A.

    Remote Sensing Digital Image Analysis provides a comprehensive treatment of the methods used for the processing and interpretation of remotely sensed image data. Over the past decade there have been continuing and significant developments in the algorithms used for the analysis of remote sensing imagery, even though many of the fundamentals have substantially remained the same. As with its predecessors this new edition again presents material that has retained value but also includes newer techniques, covered from the perspective of operational remote sensing.The book is designed as a teaching text for the senior undergraduate and postgraduate student, and as a fundamental treatment for those engaged in research using digital image analysis in remote sensing. The presentation level is for the mathematical non-specialist. Since the very great number of operational users of remote sensing come from the earth sciences communities, the text is pitched at a level commensurate with their background. The chapters progress logically through means for the acquisition of remote sensing images, techniques by which they can be corrected, and methods for their interpretation. The prime focus is on applications of the methods, so that worked examples are included and a set of problems conclude each chapter. Sources and characteristics of remote sensing image data.- correcting and registering images.- interpreting images.- radiometric enhancement of images.- geometric processing and enhancement: image domain techniques.- spectral domain image transforms.- spatial domain image transforms.- supervised classification techniques.- clustering and unsupervised classification.- Feature Reduction.- Image Classification in Practice.- Multisource Image Analysis.



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