Application

Normally, we want to do more than just look at or make appealing images. By using sensor data, we can compare and model some processes and features that would be fairly hard using only what we could see with out eyes. For instance, if we wanted to take account of the total amount of glacial ice in an area, ignoring everything else, creating a composite image of only two data types is idea - ice, and not ice. We might also want to take stock of different materials that would otherwise be very similar visually, for this there is the false image.

This image is created by assigning particular spectral patterns to glaciers which in turn highlights the glacier ice, snow, and rock.
fig. Trident glacier highlighted
            with PCA.

This image is a false color that attempts to differentiate both the snow and ice with the surrounding cold stone, much like the above. However this image ALSO makes use of infrared comparison to separate the snow from older snow and dirty glacier ice debris from the glacier proper.
fig. Trident glacier false-image.
In this image, we use infrared and near-infrared wavelengths to replace green and blue (and some minor visual editing) to create a vividly contrasted image that lets us pick out features that would be otherwise hard to distinguish. Darker areas correspond to rock and debris-filled snow and ice that reflect or transmit far less infrared than the relatively bright fresh snow and ice. In the visual spectrum, snow and ice are all but indistinguishable.

As we can see, the same image can be made to appear quiet different depending on the wavelength of light that we are using and how exactly we decide to make that new information appear.