This edition uses real examples and works through the mathematics of remote sensing to demonstrate important quantitative principles in the field. Coverage includes non-photographic sensors, digital data and global remote sensing.
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James B. Campbell, Ph.D., is Professor and Head of the Department of Geography at Virginia Tech, where he teaches courses in remote sensing and in physical geography. His research in these fields has been reported in numerous publications and supported by varied academic, governmental, and private organizations. Within the university, he has been active in support of related fields, including agronomy, geology, forestry, environmental sciences, and planning.
Preface List of Tables List of Figures List of Plates PART I. FOUNDATIONS 1. History and Scope of Remote Sensing 2. Electromagentic Radiation PART II. IMAGE ACQUISITION 3. Photographic Sensors 4. Digital Data 5. Image Interpretation 6. Land Observations Satellites 7. Active Microwave and Lidar 8. Thermal Radiation 9. Image Resolution PART III. ANALYSIS 10. Preprocessing 11. Image Classification 12. Field Data 13. Accuracy Assessment 14. Hyperspectral Remote Sensing PART IV. APPLICATIONS 15. Geographic Information Systems 16. Plant Sciences 17. Earth Sciences 18. Hydrospheric Sciences 19. Land Use and Land Cover 20. Global Remote Sensing Index About the Author
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