Description
Book SynopsisAn outgrowth of the author''s extensive experience teaching senior and graduate level students, this is both a thorough introduction and a solid professional reference.
* Material covered has been developed based on a 35-year research program associated with such systems as the Landsat satellite program and later satellite and aircraft programs.
* Covers existing aircraft and satellite programs and several future programs
*An Instructor''s Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Table of ContentsPreface.
PART I: INTRODUCTION.
Chapter 1. Introduction and Background.
PART II: THE BASICS FOR CONVENTIONAL MULTISPECTRAL DATA.
Chapter 2. Radiation and Sensor Systems in Remote Sensing.
Chapter 3. Pattern Recognition in Remote Sensing.
PART III: ADDITIONAL DETAILS.
Chapter 4. Training a Classifier.
Chapter 5. Hyperspectral Data Characteristics.
Chapter 6. Feature Definition.
Chapter 7. A Data Analysis Paradigm and Examples.
Chapter 8. Use of Spatial Variations.
Chapter 9. Noise in Remote Sensing Systems.
Chapter 10. Multispectral Image Data Preprocessing.
Appendix. An Outline of Probability Theory.
Exercises.
Index.
