An 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. This book covers existing aircraft and satellite programs, and several future programs.
DAVID A. LANDGREBE, PhD, is Professor Emeritus of Electrical Computer Engineering in the School of Electrical and Computer Engineering at Purdue University. Dr. Landgrebe is a former president of the IEEE Geoscience and Remote Sensing Society and recipient of the Society's Distinguished Achievement Award. He is the coauthor of Remote Sensing: The Quantitative Approach and a contributor to numerous other publications.
Preface. 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.