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Landsat (NASA)

The Landsat series initiated the era of Earth observation from space for non-military purposes.  Landsat-type data are now collected by satellite systems built by other countries and commercial enterprises, but Landsat data are the standard for Earth observations, and Landsat is the only system of its type with the mission to collect, archive, and distribute data of all the Earth's land surface.

The first Landsat was launched on July 23, 1972.  This satellite carried on board two instruments to look at the Earth's surface - a Return Beam Vidicon (RBV) and a Multi-Spectral Scanner System (MSS).

Landsat-1, originally called the Earth Resources Technology Satellite (ERTS-1), was followed by Landsats-2, -3, -4, -5, and -7.  Landsat-6 unfortunately failed to reach orbit.  Return Beam Vidicons and Multi-Spectral Scanner Systems were flown on the first three Landsats.  The MSS proved to be a more useful and reliable instrument that the RBV.   Landsats-4 and -5 were equipped with an MSS and an improved version of the MSS, the Thematic Mapper (TM).   Landsat-6 carried an "Enhanced Thematic Mapper" (ETM) only, and Landsat-7 is carrying an "Enhanced Thematic Mapper-plus," or ETM+.  The operating dates of the Landsat satellites and the instruments on them are listed on Table 1.
 

 
 Launched Retired Instruments
Landsat-1 (ERTS-1) July 23, 1972 January, 1978 RBV, MSS
Landsat-2 January 22, 1975 July, 1983 RBV, MSS
Landsat-3 March 5, 1978 September, 1983 RBV, MSS
Landsat-4 July 16, 1982 June, 2001* MSS, TM
Landsat-5 March 1, 1984   MSS, TM
Landsat-6 October 5, 1993 October 5, 1993 ETM
Landsat-7 April 15, 1999   ETM+

               Table 1. Landsat Satellites, their Operational Periods, and Their Instruments.
* The Landsat-4 sensors were not operational after July, 1987; the satellite was later used for maneuver testing.

 

SPOT

 

A description of the spectral bands available from the different imager products:

 
Band
 RBV MSS TM ETM+
1
 .48-.57 µm green   .45-.52 µm blue .45-.52 µm blue
2
 .58-.68 µm red   .52-.6 µm green .53-.61 µm green
3
 .69-.83 µm IR   .63-.69 µm red .63-.69 µm red
4
   .5-.6 µm green .76-.9 µm NIR .75-.9 µm NIR
5
   .6-.7 µm red 1.55-1.75 µm SWIR 1.55-1.75 µm SWIR
6
   0.7-0.8 µm IR 10.4-12.5 µm TIR 10.4-12.5 µm TIR
7
   0.8-1.1 µm IR 2.08-2.35 µm SWIR 2.1-2.35 µm SWIR
8
       .52-.9 µm panchromatic

Table 2.  Landsat Instrument Bands. IR = infrared; NIR = near infrared; SWIR = short
wavelength infrared; TIR = thermal infrared (long wavelength); and µm = micron or micrometer.

 

Three different ways of displaying the imager data:

 True Color:   For the true color rendition, band 1 is displayed in the blue color, band 2 is displayed in the green color, and band 3 is displayed in the red color.  The resulting image is fairly close to realistic - as though you took the picture with your camera and were riding in the satellite.  But it is also pretty dull - there is little contrast and features in the image are hard to distinguish.

False-Color, also called Near Infrared or NIR:   In this image, band 2 is displayed in blue, band 3 is displayed in green, and band 4 is displayed in red.  This rendition looks rather strange - vegetation jumps out as a bright red because green vegetation readily reflects infrared light energy!  It is similar to pictures taken from aircraft when using infrared film and is very useful for studying vegetation.

Short-Wavelength Infrared, or SWIR:   In this SWIR image, band 2 is displayed in blue, band 4 is displayed in green, and band 7 (or 5) is displayed in red.  This rendition looks like a jazzed up true color rendition - one with more striking colors.

 

Interpreting the spectral information:

Band 1: Blue light (0.4-0.5 microns) is scattered by the atmosphere and illuminates material in shadows better than longer wavelengths (remember, blue is the short-wavelength end of the spectrum).  Blue penetrates clear water better than other colors - see the texture of/in the water along the shore.  It is absorbed by chlorophyll, and so plants don't show up very brightly in this band.  That is why the fields all look drab and washed out.  However, it is useful for soil/vegetation discrimination, forest type mapping, and identifying man-made features, such as the airport in the lower right area of the image.
Band 2: Green light (0.5-0.6 microns) penetrates clear water fairly well, and gives excellent contrast between clear and turbid (muddy) water.  It helps find oil on the surface of water, and vegetation (plant life) reflects more green light than any other visible color.  Manmade features are still visible (note the airport).
Band 3: Red light (0.6 - 0.7 um) has limited water penetration.  It reflects well from dead foliage, but not well from live foliage with chlorophyll.  It is useful for identifying vegetation types, soils, and urban (city and town) features.
Band 4: Near IR (NIR, .7-1.2 microns, redder than red, but not visible) is good for mapping shorelines and biomass content.  It is very good at detecting and analyzing vegetation.  See how the fields that looked almost the same in bands 1, 2, or even 3 have changed dramatically in band 4.  But the airport has darkened.
Band 5: The short wavelength infrared (SWIR, 1.55 - 1.75 microns, even redder than NIR) has limited cloud penetration and provides good contrast between different types of vegetation.  It is also useful to measure the moisture content of soil and vegetation. It helps differentiate between snow and clouds.
Band 6: Thermal infrared (TIR, 5.0 - 14.0 microns, so red it "sees" warm objects; also called long-wavelength infrared (LWIR) or thermal IR) is useful to observe temperature and its effects, such as daily and seasonal variations.  It is also useful to identify some vegetation density, moisture, and cover type.  This image has only 60-meter pixels, so it is not as sharp as the other images.  Band 6 pixels on Landsat-5 are 120 meters.
Band 7: Another short wavelength infrared (SWIR, 2.08 - 2.35 microns, although somewhat longer wavelength than Band 5) has limited cloud penetration and provides good contrast between different types of vegetation (compare to vegetation in bands 4 and 5).  It is also useful to measure the moisture content of soil and vegetation. It helps differentiate between snow and clouds.

 

For more information see the Landsat tutorial

 

Bilko - Virtual global faculty for coastal & marine remote sensing (UNESCO Bilko project)
http://www.ncl.ac.uk/tcmweb/bilko/index.shtml

The UNESCO Bilko project was initiated in 1987 under UNESCO's then Marine Sciences Training and Education Programme (TREDMAR) to develop training capability in coastal and marine remote sensing through a series of computer-based learning (CBL) modules. Using a specially commissioned educational image-processing software package (Bilko) which was designed to operate on personal computers, the project has provided seven modules of computer-based lessons to over 500 marine science laboratories and educational establishments and over 600 individual users in over 70 countries around the world.

Each module is a self-contained package of:
the image processing software (Bilko),
an introductory tutorial on how to use the software,
lessons on the applications of remote sensing to oceanography and coastal management,
satellite and airborne remotely sensed images to accompany the lessons.

Downloading the UNESCO Bilko Modules
http://www.ncl.ac.uk/tcmweb/bilko/download.shtml