1. Vegetation Enhancements (continued) Lost in Feature Space!
Statistical and Feature Space Transformations

2. Learning objectives
What is a feature space and how do you construct one?
Where are plants, soils, and water found in feature space?
How can we use feature spaces to enhance vegetation spectra?
What is Principal Component Analysis (PCA)
What is Kauth’s Tasseled Cap and how is it different from PCA?

3. Feature Space Transformations
Also called “band space”
Graph with bands = axes
Difficult to visualize because feature space is n-dimensional (where n is the number of bands)
Can use feature space to enhance spectral information using mathematical transformations
Results in new axes that are not parallel to old ones
Examples are Principal Components Analysis (PCA), Kauth’s Tasseled Cap, Perpendicular Vegetation Index (PVI), and many more

4. What is a feature space??
NIR
Band
Green Band
Red Band
Blue Band

5. Why is feature space useful?
A way to visualize pixel data – a different way to see information
Can transform or analyze a feature space mathematically to isolate groups of pixels that may be related

6. Creating Feature Space Graphs
Each axis represents DNs from one satellite band; Multiple axes = multiple bands
Can plot each pixel in the feature space from an image using its DNs.

7. Interpreting Feature Space
Where is vegetation?
Where is soil?
NIR
Red

8. Principal Components Analysis (PCA)
Transforms the original data (DNs) into new “bands” that isolate important parts of the data (e.g., vegetation).
Principal component axes (PCs) must be perpendicular to one another
First 3 PCs usually contain the most useful info
Other PCs are sometimes useful for highlighting features
PC2 is usually a good vegetation index

9. Principal Components – 2 bands

10. Principal Components – 3 bands

11. Erdas Demo
Principal Components for Laramie Area

12. Kauth’s Tasseled Cap
Like PCA but axes don’t have to be perpendicular to each other
1st axis oriented towards overall scene brightness (brightness)
2nd axis oriented towards vegetation greeness (greeness)
3rd and 4th axes often called “wetness” and “yellowness” – less useful than first two.

13. Tasseled Cap (cont.) Fits all the criteria for a good vegetation index
Almost as widely used as the NDVI
Excellent index

14. Tasseled Cap

15. Creating Your Own Spectral Indices
Can create custom indices to highlight anything that makes spectra unique
Can use temporal data just like you use spectral data
Can build indices for any material, not just vegetation

16. Summary
Vegetation Indices should highlight the amount of vegetation, the difference between vegetation and soil, and they should reduce atmospheric effects
Minimize soil background effects if possible
Indices can be customized for particular applications