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Other Remote Sensing Systems - Hyperspectral Imaging

Another major advance, now coming into its own as a powerful and versatile means for continuous sampling of broad intervals of the spectrum, is hyperspectral imaging. Heretofore, because of the high speeds of air and space vehicle motion, insufficient time was available for a spectrometer to dwell on a small area of Earth's surface or an atmospheric target. Thus, data were necessarily acquired for broad bands in which spectral radiation is integrated within the sampled areas to cover ranges, such as 0.1 µm, for instance Landsat. In hyperspectral data, that interval narrows to 10 nanometers (1 micrometer [µm] contains 1000 nanometers [1 nm = 10-9m]). Thus, we can subdivide the interval between 0.38 and 2.55 µm into 217 intervals, each approximately 10 nanometers in width. These are, in effect, narrow bands. The detectors for VNIR intervals are silicon microchips, while those for the Short Wave InfraRed (SWIR, between 1.0 and 2.5 µm) intervals consist of an Indium-Antimony (In-Sb) alloy. If a radiance value is obtained for each such interval, and then plotted as intensity versus wavelength, the result is a sufficient number of points through which we can draw a meaningful spectral curve.

The Jet Propulsion Lab (JPL) has produced two hyperspectral sensors, one known as AIS (Airborne Imaging Spectrometer), first flown in 1982, and the other known as AVIRIS (Airborne Visible/InfraRed Imaging Spectrometer), which continues to operate since 1987. AVIRIS consists of four spectrometers with a total of 224 individual CCD detectors (channels), each with a spectral resolution of 10 nanometers and a spatial resolution of 20 meters. Dispersion of the spectrum against this detector array is accomplished with a diffraction grating. The total interval reaches from 380 to 2500 nanometers (about the same broad interval covered by the Landsat TM with just seven bands). It builds an image, pushbroom-like, by a succession of lines, each containing 664 pixels. From a high altitude aircraft platform such as NASA's ER-2 (a modified U-2), a typical swath width is 11 km.

From the data acquired, we can calculate a spectral curve for any pixel or for a group of pixels that may correspond to an extended ground feature. Depending on the size of the feature or class, the resulting plot will be either a definitive curve for a "pure" feature or a composite curve containing contributions from the several features present (the "mixed pixel" effect discussed in Section 13). In principle, the intensity variations for any 10-nm interval in the array extended along the flight line can be depicted in gray levels to construct an image. In practice, to obtain strong enough signals, data from several adjacent intervals are combined. Some of these ideas are elaborated in the block drawing shown here.

AVIRIS concept diagram.

Below is a hyperspectral image of some circular fields (see Section 3) in the San Juan Valley of Colorado. The colored fields are identified as to vegetation or crop type as determined from ground data and from the spectral curves plotted beneath the image for the crops indicated (these curves were not obtained with a field spectrometer but from the AVIRIS data directly).

Hyperspecrtal image of field in the San Juan Valley of Colorado. Reflectance/Wavelength Diagram of the fields shown in the previous figure.

Section 13 (p. 13-5) displays other AVIRIS images, used for mineral exploration near Cuprite, Nevada.

We know hyperspectral data are usually superior for most analyses to broader-band multispectral data, simply because so much more detail for the identifying features. In essence, spectral signatures rather than band histograms result. Plans are to fly hyperspectral sensors on future spacecraft (see Section 20). The U.S. Navy is presently developing a more sophisticated sensor called HRST and industry is also designing and building hyperspectral instruments such as ESSI's Probe 1.

I-25: In your own words, using a single sentence, state the major advantage of hyperspectral sensors over broad band sensors. ANSWER

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Primary Author: Nicholas M. Short, Sr. email:

Collaborators: Code 935 NASA GSFC, GST, USAF Academy
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