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A Multi-spectral image is one that captures image data at specific wavelengths across the electromagnetic spectrum. The wavelengths may be separated by filters or by the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, such as infrared. Multi-spectral imaging can allow extraction of additional information that the human eye fails to capture with its receptors for red, green and blue. It was originally developed for space-based imaging.

Multi-spectral images are the main type of images acquired by Remote sensing (RS) radiometers. Multi-spectral is the opposite of panchromatic. Usually satellites have 3 to 7 or more radiometers (Landsat has 7). Each one acquires one digital image (in remote sensing, called a scene) in a small band of visible spectra, ranging 0.7 µm to 0.4 µm, called red-green-blue (RGB) region, and going to infra-red wavelengths of 0.7 µm to 10 or more µm, classified as NIR-Near InfraRed, MIR-Middle InfraRed and FIR-Far InfraRed or Thermal. In the Landsat case the 7 scenes comprise a 7 band multi spectral image. Multispectral images with more numerous bands or finer spectral resolution or wider spectral coverage may be called "hyperspectral" or "ultra-spectral".

This technology has also assisted in the interpretation of ancient papyri such as those found at Herculaneum, by imaging the fragments in the infrared range (1000nm). Often the text on the documents appears to be as black ink on black paper to the naked eye. At 1000nm, the difference in light reflectivity makes the text clearly readable. It has also been used to image the Archimedes Palimpsest by imaging the parchment leaves in bandwidths from 365-870 nm and then using advanced digital image processing techniques to reveal the under text of Archimedes work.

The availability of wavelengths for remote sensing and imaging is limited by infrared window and optical window.

Contents

Spectral bands

The wavelengths are approximate; exact values depend on the particular satellite's instruments:

  • Blue, 450-515..520 nm, used for atmospheric and deep water imaging. Can reach within 150 feet (46 m) deep in clear water.
  • Green, 515..520-590..600 nm, used for imaging of vegetation and deep water structures, up to 90 feet (27 m) in clear water.
  • Red, 600..630-680..690 nm, used for imaging of man-made objects, water up to 30 feet (9.1 m) deep, soil, and vegetation.
  • Near infrared, 750-900 nm, primarily for imaging of vegetation.
  • Mid-infrared, 1550-1750 nm, for imaging vegetation and soil moisture content, and some forest fires.
  • Mid-infrared, 2080-2350 nm, for imaging soil, moisture, geological features, silicates, clays, and fires.
  • Thermal infrared, 10400-12500 nm, uses emitted radiation instead of reflected, for imaging of geological structures, thermal differences in water currents, fires, and for night studies.
  • Radar and related technologies, useful for mapping terrain and for detecting various objects.

Spectral band usage

For different purposes, different combinations of spectral bands can be used. They are usually represented with red, green, and blue channels. Mapping of bands to colors depends on the purpose of the image and the personal preferences of the analysts. Thermal infrared is often omitted from consideration due to poor spatial resolution, except for special purposes.

  • True-color. Uses only red, green, and blue channels, mapped to their respective colors. A plain color photograph. Good for analyzing man-made objects. Easy to understand for beginner analysts.
  • Green-red-infrared, where blue channel is replaced with near infrared. Vegetation, highly reflective in near IR, then shows as blue. This combination is often used for detection of vegetation and camouflage.
  • Blue-nearIR-midIR, where blue channel uses visible blue, green uses near-infrared (so vegetation stays green), and mid-infrared is shown as red. Such images allow seeing the water depth, vegetation coverage, soil moisture content, and presence of fires, all in a single image.

Many other combinations are in use. Near infrared is often shown as red, making vegetation covered areas appear red.

Multispectral Data Analysis Software

See also

References

  • Harold Hough: Satellite Surveillance, Loompanics Unlimited, 1991, ISBN 1-55950-077-8
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