Terrestrial remote sensing toolkit

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BRG The University of Queensland
Fundamentals

- Main page
- Pre-processing
- Field data collection
- Mapping approaches
  - Manual delineation
  - Object based analysis
  - Supervised class.
  - Unsupervised class.
  - Inverse modelling
  - Regression analysis
- Change and trends
- Delivery

# Supervised classification

### How does supervised classification work?

Supervised classification uses field data to derive groups of pixel values within an area of interest that are assumed to have the same mapping category and similar spectral reflectance signatures. The training signatures for each category to be mapped are then quantitatively compared to each pixel in the image, pixels are assigned to the mapping class that their spectral signature is most similar to.

Supervised classification sequence: Insert caption here.

## References:

Jensen, JR (2005). Introductory digital image processing: a remote sensing perspective. Third edition, Prentice Hall: 316p.