1. Introduction to Remote Sensing of the Environment Bot/Geog 4111/5111
Ken Driese
Dept. of Botany

2. Group Activity: Solving Remote Sensing Problems
Your group must speculate about how to accomplish one of the following using remote sensing! You must use only your brains! You cannot use the internet or other resources.
How could you assess the effect of drought on plant biomass in California?
How could you map sage grouse habitat in Wyoming?
How could you measure ground deformation in Yellowstone that might signal an eruption of the feared supervolcano?
How could you use remote sensing to gather intelligence about whether the recent election in Venezuela was legitimate?
How could you find your own private hot spring deep in the wilderness?

3. Course Scope Electromagnetic radiation
Emphasis on satellite remote sensing
Emphasis on land management applications – particularly vegetation mapping and monitoring
Introduction to specialized types of remote sensing
Hands-on skills: image processing and analysis

4. Types of Remote Sensing -- Sensors
Aerial Photography
Film, Digital, Aerial, Orbiting
Multispectral Imaging
Hyperspectral Imaging
Active Remote Sensing
Thermal Imaging

5. Types of Remote Sensing – Applications
Terrestrial
Marine
Atmospheric
Planetary
Astronomy

6. The History of Remote Sensing
Historical context is important for understanding the present and predicting the future.

7. The Electromagnetic Spectrum

8. Reflectance

9. Identifying Materials: Spectral Differences

10. Digital Data vs. “Pictures”
Satellite data are numbers that represent the strength of reflected light hitting the sensor, just like your digital camera
Satellite “pictures” are visualizations of these data

12. Satellite Basics What so satellites measure?
What is satellite resolution?
How do orbital characteristics affect data collection?
How do satellites gather data?

13. Survey of Commonly Used Satellites
Landsat
Hyperion
Ikonos/Quickbird
AVHRR
MODIS
IRS
SPOT
etc.
From

14. High spatial resolution (E.G., Worldview, Quickbird
Aerial Photograph
Grand Prismatic Pool, Yellowstone
Google Earth

15. Lower spatial resolution (e.g., MODIS)

16. Atmospheric Corrections

17. Geometric Corrections

18. Image Enhancement – Spectral Indices
What do these images show you?

19. Aerial Photography

20. Image Classification (Making Maps)
What does MMU mean?
What is “land cover”?

21. Accuracy Assessment
Corn User’s Accuracy = 25/32

22. Change Detection
2003
1989
Also see THIS SITE

23. Using GIS to Improve Maps

24. Hyperspectral Imaging – “hyper” amounts of spectral data
black - blue - green - yellow - red (brightest)
Area on right side, where red occurs in NIR is probably areas of dense vegetation.
bright areas in MIR are different minerals

25. Thermal Remote Sensing
Death Valley thermal image with north to right

26. Radar and Lidar

27. Global Change