The successful application of remote sensing techniques requires knowledge and skills drawn from several scientific disciplines. Specialists in specific areas of the field require a broad range of expertise, encompassing physics and optics, mathematics, statistics and digital computers. Treats the specialized area of digital image processing of remotely-sensed data in relation to these and other fields, providing a thorough understanding of its functions, uses and capabilities. The opening section discusses the physical principles of remote sensing, followed by a description of satellite platforms currently in use as well those under development. Also examines the characteristics of digital computers as they relate to the processing of remotely-sensed image data. Examines particular topics within the general field of processing remotely-sensed data and their application to a range of problems in the environmental and earth sciences.
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Remotely-sensed images of the Earth’s surface provide information about the geographical distribution and properties of natural and cultural features. Computer processing takes place after the images have been collected, and depends on their physical properties and the applications for which they will be used. Computer Processing of Remotely-Sensed Images is the third edition of this highly regarded textbook.
This fully revised and updated edition deals with the mechanics of processing remotely-sensed images. Presented in an accessible manner, this book covers a wide range of image processing and pattern recognition techniques. A number of examples are included on the accompanying CD to illustrate the practical use of specific techniques. New topics include LiDAR data processing, SAR interferometry, the analysis of imaging spectrometer image sets and the use of the wavelet transform.
The accompanying CD-ROM has been further developed to include:
This is an essential textbook for upper level undergraduate and Masters students taking courses in Remote Sensing, in departments of Geography, Earth and Environmental Science. Researchers and professionals working on the processing and classification of with remotely-sensed data, will also greatly benefit from the guidance contained in this text.
Paul Mather has been Professor of Geographical Information Science at The University of Nottingham, UK since 1988. BA (Cambridge), PhD (Nottingham). Main research interests: multivariate analysis of spatial data (Computational Methods of Multivariate Analysis in Physical Geography, Chichester, John Wiley, 1976) and digital image processing applied to remotely sensed data, particularly algorithms for classification and pattern recognition (Classification Methods for Remotely Sensed Data, with B. Tso, London, Taylor and Francis, 2001).
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