ES 351, ES 771, ES 775
|MSS (1-3)||4, 5, 7||B, G, R||Std. false color|
|MSS (4-5)||1, 2, 4||B, G, R||Std. false color|
|TM (4-5, 7)||1, 2, 3||B, G, R||Natural color|
|TM (4-5, 7)||2, 3, 4||B, G, R||Std. false color|
|TM (4-5, 7)||1, 2, 7||B, G, R||Special composite|
|TM (4-5, 7)||2, 3, 5||B, G, R||Special composite|
|TM (4-5, 7)||3, 7, 5||B, G, R||Special composite|
|TM (4-5, 7)||4, 5, 7||B, G, R||Infrared composite|
|Single-band, black-and-white image of southern Saskatchewan, Canada. Field of view about 150 km across. Short-infrared band depicts active vegetation in light gray tones; bare/fallow ground is dark gray; water bodies are black. Landsat MSS band 7, acquired 5/78; image from EROS Data Center.|
|Metropolitan Kansas City region. This image is a "natural color" composite that simulates normal color appearance of the scene. The urban area is depicted in white (highways, buildings, railroads), muddy water is brown, and vegetated areas are shown in dark green. Compare with the standard false-color version (below) of this same scene. Landsat TM bands 1,2,3; acquired 3/83; image from NASA GSFC.|
|Kansas City metropolitan region. Standard false-color composite image formed from green, red, and short-infrared bands, color coded as blue, green, and red. Active vegetation appears red and pink, and water bodies are black. Urban structures appear in white to light blue shades. Compare with the natural-color version (above) of this same scene. Landsat TM bands 2,3,4; acquired 3/83; image from NASA GSFC.|
|Special composite of visible and mid-infrared bands. The visible bands penetrate water and show suspended sediment in surface water. Volcanic mountains are visible around the lake. Landsat TM bands 1,2,7; acquired 9/84; image from NASA GSFC.|
|The edge of the Andes Mountains is seen flanked by extensive alluvial fans that form relatively flat surfaces. Straight lines and geometric designs (left center) are the archeologic "Nazca lines" of prehistoric origin. This special composite employs visible and mid-infrared bands. Landsat TM bands 2,3,5; image from NASA GSFC.|
|Infrared false-color composite of White Sands, New Mexico. The White Sands are dunes composed of gypsum sand blown from a nearby dry lake bed. In this image the gypsum dunes appear light blue, and the sand source area is dark blue. Landsat TM bands 4,5,7; image from NASA GSFC.|
|TM bands 1 (blue), 4 (near-infrared) and 5 (mid-infrared) color coded as blue, green and red. Active vegetation appears bright green and yellow-green. CBWA = state wildlife area, TNC = The Nature Conservancy. Image processing by JSA.|
|TM bands 1 (blue), 2 (green) and 3 (red) color coded as blue, green and red. This is a natural-color composite based on the visible bands.|
|TM bands 2 (green), 3 (red) and 4 (near-infrared) color coded as blue, green and red. Active vegetation appears bright red in this standard false-color composite.|
|TM bands 2 (green), 5 (mid-infrared) and 7 (mid-infrared) color coded as blue, green and red. Active vegetation appears green. One of your author's favorite false-color composites with naturalistic color. Note one bad line of data (band 7), which appears as an orange stripe near the top.|
Spectral signatures are how we "see" the natural or false color of objects. Various objects may be discriminated or classified—rock types, vegetation, water bodies, snow and ice, etc. This is a powerful method for interpreting Landsat data, but classification techniques must be used with some caution. The spectral signatures of objects are not constant; signatures vary with time of year, amount of solar illumination, geographic locations, and many other factors. Thus, a classification technique that works well in one situation may not be appropriate in other circumstances.
|Mt. McKinley, Alaska portrayed with Landsat image draped over a block model of landscape topography. The oblique view is created from a digital elevation model (DEM), and color coding comes from the Landsat image. Large valley glaciers with medial moraines are visible in foreground. Landsat TM bands 2,3,4 + DEM; image from NASA GSFC.|
Any of these approaches requires considerable computation, in which the remotely sensed data must be rectified for accurate fit onto the ground coordinate system of the DEM. Resampling of pixel size, shape, and position may be necessary. The effort necessary to produce such merged images is well worth the investment of time. Landsat/DEM images may be particularly valuable for geomorphic interpretation.
Return to Landsat remote sensing.