These single band, spectral class maps are the result of the unsupervised Isodata K-means clustering procedures imposed on each TM/ETM+ triplicate data set. The resulting spectral classes have been color coded to simulate a false color infrared photograph for the spring, summer, and/or fall seasons. This has been accomplished by using an RGB 3-band rendition of either 4-3-2 or 4-3-1 from the Landsat TM/ETM+ sensor for each of the seasonal images.
Since a TM/ETM+ triplicate data set was used for each of the Path/Row scene areas, it is possible to produce a pseudocolor spectral class map for each season. However, they have been generated only for those TM/ETM+ scenes which exhibited overall, optimum scene quality and therefore some Path/Row scene areas have two rather than three seasonal images. Consult the 1999-2000 TM Coverage Map at this web site for the specific acquisition dates.
The pseudocolor spectral class map files are provided in GeoTIFF format, and are projected to transverse Mercator with a UTM zone 16 grid and WGS84 datum (same as NAD83). Each 3-band RGB combination used is listed in the filename as either 4-3-2 or 4-3-1.
The following two sections have been provided for users that are not familiar with the Landsat TM/ETM+ sensor and color infrared technology and interpretation.
The TM/ETM+ spectral bands were chosen after years of analysis of remote sensing data for their value in water penetration, discriminating vegetation types and vigor, plant and soil moisture measurements, differentiation of clouds, snow, and ice, and identification hydrothermal variation in certain rock types. In addition, the effects of atmospheric scattering and absorption determine the placement of bands in the electromagnetic spectrum. The wavelengths listed below are in micrometers (Ám), and for comparison 1 Ám is equivalent to 1/1,000 millimeter in length (from Jensen 1996):
Band 1: 0.45 - 0.52 Ám (blue). Provides increased penetration of water bodies as well as supporting analyses of land use and land cover, soil, and vegetation characteristics. The shorter-wavelength cut-off is just below the peak transmittance of clear water, while the upper-wavelength cut-off is the limit of blue chlorophyll absorption for healthy green vegetation. Wavelengths below 0.45 Ám are substantially influenced by atmospheric scattering and absorption.
Band 2: 0.52 - 0.60 Ám (green). This band corresponds to the green reflectance of healthy vegetation and is spanning the region between the blue and red chlorophyll absorption bands.
Band 3: 0.63 - 0.69 Ám (red). This red chlorophyll absorption band of healthy green vegetation is one of the most important bands for vegetation discrimination. In addition, it is useful for soil-boundary and geological boundary mapping. Band 3 may exhibit more contrast than bands 1 and 2 because the effect of the atmosphere is reduced. The 0.69 Ám cut-off represents the beginning of a spectral region from 0.68 to 0.75 Ám where vegetation reflectance crossovers occur that can reduce the accuracy of vegetation studies.
Band 4: 0.76 - 0.90 Ám (near infrared). For reasons discussed above, the lower cut-off for this band was placed above 0.75 Ám. This band is especially responsive to the amount of vegetation biomass present in a scene. It is useful for identification of vegetation types, and emphasizes soil-crop and land-water contrasts.
Band 5: 1.55 - 1.75 Ám (middle infrared). This reflective-IR band is sensitive to the amount of water in plants, which is useful in drought studies and plant vigor studies. In addition, this band can be used to discriminate between clouds, snow, and ice which makes it important in hydrologic research, as well as being able to remove the effects of thin clouds and haze.
Band 7: 2.08 - 2.35 Ám (middle infrared). This band is used to discriminate between geological rock formations. It is particularly effective in identifying zones of hydrothermal alteration in rocks.
Band 6: 10.4 - 12.5 Ám (thermal infrared). This band measures the amount of infrared radiant flux (heat) emitted from surfaces. The apparent temperature is a function of the emissivities and true (kinetic) temperatures of surface objects. Therefore, band 6 is used in locating geothermal activity, thermal inertia mapping, vegetation classification, vegetation stress analysis, and in measuring soil moisture. It is often not utilized because of its lower spatial resolution as compared to bands 1-5, and 7, and special processing is necessary to incorporate it into natural resource applications.
Although black/white (panchromatic) imagery has long been used as the standard for interpretation, most natural resource applications are improved by using color and especially color infrared (CIR) imagery. This is because the human eye can discriminate many more shades of color than gray levels, and color imagery naturally mimics human experience in everyday interpretation of the environment. Standard color imagery records the "visible" portion of electromagnetic energy (approximately 0.4-0.7 Ám), which is the same reflected radiation perceived by the human eye. In CIR imagery the range of sensitivity has been extended into the "invisible," reflected near infrared portion of the electromagnetic spectrum (approximately 0.7-0.9 Ám). What this means is that the discrimination of most landscape features is enhanced using CIR imagery, including the following phenomena:
CIR imagery does not record colors in the environment as they would be seen with normal color photography. For this reason, CIR photography is often referred to as "false color." Here are some representative surface features and how they may likely appear on the pseudocolor spectral class maps:
|Winter wheat, oats, rye grass; urban lawns and open space; emerging tree canopies in early spring and deciduous wooded areas during late spring-early fall.||Bright pink to dark red colors|
|Non-turbid surface water; exposed wet soils; asphalt rooftops and parking lots.||Dark gray to black|
|Dark, saturated soil surfaces; urban structures; deciduous wooded areas with little/no leaf canopy; turbid surface water.||Light to dark, blue-green tones|
|Exposed, better drained and light colored soils; barren land; commercial buildings, concrete and gravel parking lots and roadways.||Light colored to white|
Jensen, J.R., 1996. Introductory Digital Image Processing, Prentice-Hall.