Classification Methods for Remotely Sensed Data [Paperback]

Paul Mather (Author), Brandt Tso (Author)

Book Description

Publication Date: December 1, 2001 | ISBN-10: 0415259096 | ISBN-13: 978-0415259095 | Edition: 1

Remote sensing is an integral part of geography, GIS and cartography, used by academics in the field and professionals in all sorts of occupations. The 1990s saw the development of a range of new methods of classifying remote sensing images and data, both optical imaging and microwave imaging. This comprehensive survey of the various techniques pulls together information from a range of sources and sets it in the context of the basic principles. There is an emphasis on new methods, including neural networks (especially artificial neural networks), fuzzy theory, texture and quantization, and the use of Markov random fields. Students in GIS and remote sensing should find this an essential read when learning about and dealing with new developments in the field. It is concise and accessible and the authors conclude with coverage of the state-of-the-art topics of multisource data analysis, evidential reasoning and genetic algorithms. Including a full color section and basic remote sensing theory, this book will prove invaluable for advanced undergraduate students and graduates/researchers in the field. There is very little published in this field yet, and there is distinct need for such an analysis of this fast-growing area.

Editorial Reviews

Review

… a very useful addition to the shelf of anyone engaged in remote sensing image analysis. It is suitable for both students and practitioners.
—Michael Collins,  in GEOMATICA, Vol. 63, No. 4

--This text refers to the Hardcover edition.

From the Author

This book provides a comprehensive survey of image classification techniques. Beginning with a general, introductory review of basic principles, the book aims to bring together information from a range of sources and set it in the context of basic principles. There is an emphasis on new methods, including the use of artificial neural networks, procedures based on fuzzy theory, techniques of texture quantisation, the use of Markov random fields in modelling context, and the use of multiple classifiers.

See all Editorial Reviews

Product Details

• Paperback: 352 pages
• Publisher: CRC Press; 1 edition (December 1, 2001)
• Language: English
• ISBN-10: 0415259096
• ISBN-13: 978-0415259095
• Product Dimensions: 9.4 x 6.4 x 0.6 inches
• Shipping Weight: 1.3 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #3,514,562 in Books (See Top 100 in Books)

More About the Author

Professor Brandt Tso currently serves in information management department, Management College, National Defense University.
Readers who are interested in remotely sensed data processing programmes (written in C language) please refer to the following linkage http://homepage.ntlworld.com/paul.mather/book.html
All are freeware and welcome to use, however, copyright is reserved.

Customer Reviews

Most Helpful Customer Reviews

2 of 6 people found the following review helpful:

5.0 out of 5 stars Classification Methods for Remotely Sensed Data, July 1, 2002

By 

Mikael Kamp Sørensen (Denmark) - See all my reviews

This review is from: Classification Methods for Remotely Sensed Data (Hardcover)

...I must say that it is the best book on remote sensing I have ever come across...