Remote Sensing of the Environment
Geosciences 4050
Instructions: Please take your time and answer each question as it pertains to the science of
remote sensing and geospatial analysis. Also, note the total points for each question reflects
the level of effort. Make sure that you are constructing well written sentences and paragraphs.
Please use the ERDAS Imagine Field Guide, your text book and other reputable sources to
answer the questions. Do not cut and paste from web-sites except for diagrams. Note all
sources.
1. Discuss the merits of preprocessing techniques that improve the visual appearance
of an image but do not alter its basic statistical properties. Are visual qualities
important in the context of image analysis? (10 points)
2. Discuss the advantages and disadvantages of fine-resolution data relative to coarser
spatial, spectral and radiometric detail? (10 points)
3. Describe in a flow chart or diagram the steps required to read data in a BIP format,
and then organize them in a BSQ structure. (10 points)
4. Why are enhanced images usually not used as input for other analyses? (10 points)
5. Explain why different band (channel) combinations are useful for visual
interpretation and digital analysis. (10 points)
6. Why are the orbits of land observation satellites relatively low compared to those of
communications satellites? (5 points)
7. What are some of the pros and cons of private ownership of high-resolution satellite
remote sensing systems? (10 points)
8. Describe the similarities and differences between the Landsat 8 satellite and the
QuickBird satellite? (10 points)
9. Describe the ideal conditions for achieving maximum spatial resolution? (10 points)
10. How are spatial resolution, spectral resolution and radiometric resolution
interrelated? Is it possible to increase one kind of resolution without influencing the
others? (15 points)
11. Compare and contrast the two types of image classification (10 points).
12. What is the difference between parametric and nonparametric (10 points).
13. Define the following statistical classifiers (3 points each):
Parallelepiped
Maximum Likelihood
Centroid (K-Means)
14. What are training samples and how are they collected (5 points)?
15. What is ancillary data and how is it useful to remote sensing (5 points)?
16. Discuss how the resolution of satellite imagery might affect the image classification
process (10 points)?
17. What is accuracy assessment and describe how it is accomplished (10 points)?
18. What is albedo and why is it important to remote sensing (5 points)?
19. Please take your time and think about what the future of remote sensing and what it
might bring to our modern society. Also, think about the applications and benefits of
remote sensing. Write down these thoughts in a consistent and coherent story (10
points).
20. In your own words describe how you might use remote sensing technology in your
professional career to solve real world problems? Please take your time and think about
this question (10 points).