DescriptionAn 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.
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.