![]() The spectral resolution required for a specific sensor depends on the spectral characteristics of the material you are trying to identify. Although it can have many bands covering the visible to thermal spectrum, it cannot produce a continuous spectrum of an object like a hyperspectral sensor can. The following figure shows how a given pixel from a multispectral image only covers discrete spectral bands. Quality spectrometers are usually designed so that the band spacing is approximately equal to the FWHM, which explains why spectral sampling is often used interchangeably with spectral resolution. Spectral sampling is a separate concept that refers to the band spacing, or the quantization of the spectrum at discrete steps. This is known as the full-width-half-maximum (FWHM). More specifically, it refers to the width of an instrument response (band pass) at half of the band depth. Spectral resolution refers to the width of each band within the captured spectrum. Compare this to broadband multispectral sensors such as Landsat 8 OLI, which has nine spectral bands and a spectral resolution of 106 nm. Airborne and satellite imaging spectrometers can have up to several hundred bands with a spectral resolution of 10 nanometers (nm) or narrower. Hyperspectral sensors-more commonly known as imaging spectrometers-collect spectral information across a continuous spectrum by dividing the spectrum into many narrow spectral bands. See the " Preprocessing AVIRIS Tutorial" for the steps used to create the reflectance image. These are primarily water vapor bands that cause spikes in the reflectance curve. 53 bands marked as "bad" in the ENVI header file.Processed with FLAASH to remove atmospheric effects and to create a surface reflectance image in ENVI format.This image was processed as follows, resulting in the file CupriteReflectance.dat: The full radiance scene is available from NASA/JPL. The scene was collected from an ER-2 aircraft on August 8, 2011. The sample image covers the Cuprite Hills area of southern Nevada, an area with diverse mineral types. AVIRIS data files are courtesy of NASA/JPL-Caltech. The image used in this exercise was collected by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) sensor. You will also use some mineral spectral library files that are included with your ENVI installation. Region of interest (ROI) file with known mineral occurrences Tutorial files are available from our ENVI Tutorials web page or on the ENVI Resource DVD in the hyperspectral directory. The names of some menu items and the appearance of plot windows will vary, depending on the version you use. Use this tutorial with ENVI 5.1 or later. Design color images to discriminate mineralogy.Extract mean image spectra from regions of interest (ROIs).Compare image spectra to known library spectra.Analyze spectral profiles from AVIRIS reflectance data.This tutorial introduces you to visualization and interactive analysis tools for working with hyperspectral data.
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