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Engineering - Electronics & Electrical Engineering | Remote Sensing Digital Image Analysis - An Introduction

Remote Sensing Digital Image Analysis

An Introduction

Richards, John A., Jia, Xiuping

4th ed. 2006, XXV, 439 p. 197 illus.


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Remote Sensing Digital Image Analysis 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 fourth edition has been developed to reflect the changes that have occurred in this area over the past several years. Its focus is on those procedures that seem now to have become part of the set of tools regularly used to perform thematic mapping. As with previous revisions, the fundamental material has been preserved in its original form because of its tutorial value; its style has been revised in places and it has been supplemented if newer aspects have emerged in the time since the third edition appeared. It still meets, however, the needs of the senior student and practitioner.

Content Level » Research

Keywords » Geoinformationssysteme - Radio - Sensor - classification - computer - digital elevation model - remote sensing

Related subjects » Earth Sciences & Geography - Electronics & Electrical Engineering - Geographical Information Systems - Geophysics & Geodesy - Image Processing - Signals & Communication

Table of contents 

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.- Multisource, Multisensor Methods.- Interpretation of Hyperspectral Image Data.

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