Module 10 - Remote Sensing - Supervised Classification

Supervised Land Cover Classification and Distance File Map

We worked with unsupervised classification last week in Remote Sensing, in which the programs determine classes of pixels that share similar spectral signatures, without prior input from the human analyst. Any adjustments are done afterwards.  This week we worked with supervised classification.  With this process, we "train" the software by identifying samples of particular classes of land cover, then let the programming assign the rest of the pixels in the image based on their similarity to the signatures of the samples.  The map at right was classed from an image using this type of process, after setting up 16 samples representing 8 unique land cover classes (as shown on the map legend at left).

The map was created using a band combination of Red = Band 4, Green = Band 5 and Blue = Band 6.  These are all bands in the Near- to Mid-Infrared part of the spectrum.  They were chosen because they display the classes most distinctly and there is little overlap between the signatures.

 The small grey-scale map at the bottom is called a Distance File map.  It shows how well our classification signatures match the signatures of the pixels from the original image.  The dark areas are those features which have a signature that matches the class spectral signatures best, while the white areas are those that do not fall into one of the classes created from the samples.  It is called a Distance file because it refers not to spatial distance on the ground, but rather distance on an XY plot between defined classes and the image pixels.