This is the third of five lectures being devoted to exploring the characteristics of remotely sensed imagery. In today's lecture we will consider spectral resolution.

Spectral resolution is defined as the width of the region of the EM spectrum recorded as one 'band' or, in some cases, a "channel". Typically this band width is related to the number of wavelength bands recorded by the sensor. Modern sensors can be divided into three broad classes based on their spectral resolution:

• panchromatic (one very wide band, typically covering a significant portion of the visible spectrum)
• multispectral (several coarse bands, typically limited to 15 or fewer bands)
• hyperspectral (many discrete, fine bands, typically far more bands than a multispectral system)

In today's lecture I'll provide an overview of spectral resolution and provide examples of the three broad classes. Recall that in Lecture 3 I reviewed the names for each of the different spectral regions (e.g., visible, IR, microwave).

There are several informative web sites that should help you understand how spectral resolution varies in different satellites, and why satellites are designed with different spectral resolutions.

• Overlaying spectral curves on sensor bands (and a description of the MODIS bands).
• A good discussion of SNR (signal-to-noise ratio)
• A library of spectral reflectance curves.
• False colours (i.e., band combinations).
• Some resources for students created by NASA.
• A description of the Gambit KH-8 satellite (aka "Key Hole")--a US photographic surveillance system.
• How remote sensing is used in food industry!

Text: Chapter 2.5.1: Sensing properties