Answers

The human eyeI-1: The eye shares functions common to a camera. To the left is a diagram of the human eye. Key components are the cornea, the iris and pupil, the lens, and the retina. Light from objects close to distant pass through the outer layer, or sclera, of the eye into the cornea which encloses a liquid, the vitreous humor whose index of refraction is 1.3 (air is 1.0). Refraction (bending) of light occurs in the cornea, and is diverted inward to pass through the iris (which has some distinctive color, which varies in individuals according to precise composition of a pigment). The iris responds to varying amounts of light (brightness) by diameter changes of the pupil (as it enlarges [gap between the lines in the illustration defines the circular pupil], more light is admitted). This refracted light now passes through the lens, a transparent material that serves to focus light; light is further refracted as it passes across the curved boundaries. Focusing is done by changing the shape (thickness) of the lens through the action of the ciliary muscle; in a thickened mode, the lens focuses near objects. These changed light rays now pass through the gelatin-like vitreous humor onto the retina which can detect rays extending against a hemisphere more than 180° in arc. Most of the focused light strikes within 20° of a central point called the fovea. The retina (somewhat analogous to camera film) consists of layers that include nerve cells and light receptors called cones and rods. Individual cones, in a central region called the macula, are receptive to red, green, or blue light (because of pigments sensitive to each); the rods are tuned to variations in brightness and respond by sending signals in shades of gray. The processed light is converted to electrical impulses that move to the optic nerve (itself about 20° off center, in the eye's blind spot) and eventually to the brains visual center, where the inverted image on the retina is converted to upright and the color and brightness signals are combined to yield what the eye perceives to be an image of the external world. (Note: the eye lens focuses by changing thickness; the camera by forward/backward movements). Human vision extends from a spectral region (the visible) that covers wavelengths of 400 to 700 nanometers (a nanometer is 10-9, or a billionth, of a meter). Under contrasting conditions, the eye is capable of seeing a line 2 millimeters wide at a distance of 5 meters. BACK


I-2: Acquisition/measurement; data/information; properties; phenomenon,...material; recording device; not in contact; measuring fields.radiation; instruments. BACK


I-3: Geospatial connotes the distribution of something in a geographic sense; it refers to entities that can be located by some co-ordinate system. The three terms "feature; object; class" have different but somewhat overlapping meanings. Feature can refer to "overall appearance", "mark", or "characteristic", and/or to a set of measurable properties, or, more narrowly, to a specific geometric or geomorphic entity on the surface of a planet such as Earth. Object relates to a single entity, of a physical nature, capable of being sensed (e.g., seen or touched), to which a descriptive name can be given, such as "house", "road". Class has a more general connotation, pointing to a group of features or objects of identical or similar types that have taxonomic significance; examples are "forest"; "urban"; "mountains". Classes can be hierarchical, that is, can be subdivided into subclasses; thus "urban" includes "inner city/suburbia", "road networks", "neighborhoods", "shopping centers", etc. The term "theme" is often interchangeable with "class". The term "material" is sometimes a substitute for any of the other terms but this really should be used only to refer to the physical nature of a class or object that affects its spectral properties.BACK


I-4: One might think there is an error, at first glance. The delta E on the left denotes a change in energy level. As an equation, there should be a delta variable on the right, in this case "v" (this is the letter "vee" which here is similar in appearance to the small Greek letter "nu" [ν] that was not available on the html editor; some textbooks use the letter "f" for frequency). This seems to give an inconsistency in which both E and delta E = hv. But, in effect, this is "built in" to the meaning of the equation: when there is a change in energy level, as for example an orbiting electron in an atom moving to a higher energy state, this change is represented by some delta E which has its characteristic frequency. For the formula: E = hv, at some energy level, there is a corresponding frequency at some value unique to the discrete energy value for that particular E. BACK


I-5: Simply put "Longer is lower", meaning that longer wavelengths are associated with lower energy levels. It follows that "Shorter is higher". BACK


I-6: The appropriate equation is E = hc/wavelength, or Wavelength (in meters) = hc/E. Thus, Wavelength = (6.626 x 10-34) (3.00 x 108)/(2.10 x 10-19) = 9.4657 x 10-7m = 946.6 nm; = 9466 angstroms; = 0.9466 µm (in the near-infrared region of the spectrum). BACK


I-7: Here the operative equation is: Wavelength = c/frequency. Thus, Wavelength = (3.00 x 108) (120 x 106) = 2.5 meters. BACK


I-8: Go first to the peak close to 500 nanometers of the irradiance curve for sunlight as it reaches the outer atmosphere. On the ordinate, its spectral irradiance reads 2100. For the sea level irradiance curve at the same peak position, the value is estimated to be 1300. Thus, the percent loss is: (2100 - 1300)/2100 x 100 = 38%. Note that at most other spectral locations, the loss is less. BACK


I-9: 1000 nm/micrometer; 10000 A/micrometer. BACK


I-10: (Intervals in micrometers). 1) Visible-Near IR (0.4 - 2.5); 2) Mid-IR (3 - 5); 3) Thermal IR (8 - 14); 4) Microwave (1 - 30 centimeters). BACK


I-11: (In micrometers) a) 0.8 - 0. 95; b) 0.8 - 0.95; the percent reflectance is less than grasslands; c) 0.59; d) 0.57. The four classes should be distinguishable at 0.6 micrometers, provided the instrument's sensitivity (ability to distinguish reflectances of small differences) is 5% or better. BACK


I-12: In the visible, the red sand (a rock material) is brighter than either vegetation type (water is least bright); however some rocks can be darker (such as black shales). In these curves this reverses in the Near-IR (1.2 micrometers), so that normally vegetation will be brighter (here, pinewoods is brighter) in this part of the Near-IR relative to most rock types. BACK


I-13:By extrapolating to the abscissa and ordinate, the values for 0.5 and 1.1 micrometers respectively are a) water:10 and 1; b) rock (sand): 40 and 32; c) grasslands: 20 and 40. When these are plotted in the diagram, both rock and vegetation are about equidistant from the unknown X. This is a case where one might choose a different wavelength. Try 1.0 micrometers and see if discriminating between those two classes improves. The conclusion you should now reach is a strong argument for having larger numbers of spectral bands (each can also cover a narrower interval of wavelengths) on the sensor. BACK


I-14: In a false color composite, for example, the forest and growing crops are likely both to appear red (we will find out why later in this Section). But, in an image most fields tend to have straight boundaries - usually rectangles - whereas forests commonly are irregular in shape and distribution. Shape is a prime tool by which an interpreter can distinguish classes that have similar spectral characteristics but are distinct in their outlines. Look at the Salt Lake City image again - note the widespread forests in the mountains and the small, regularly-shaped fields in the lowlands. BACK


I-15: For the Non-Vegetated classes, at ~0.87 micrometers; Vegetated at ~0.78 micrometers. BACK


I-16: The gray levels will depend on the specific point locations you chose. As a general rule, a feature or object or patch seen in a filtered aerial black and white photo (or a space image) will be light-toned if its color is close to that of the filter's color, and will be varying levels of darker in images made with other colors depending on color proximity in the visible light scale (red is spectrally farther from blue than from green). BACK


I-17: The white feature is light (clear-toned) in all three color layers (or projections) and represents a white object, such as light sand, on the ground. The blue represents materials that are brightest in shorter wavelengths and diminish in reflectance in longer visible wavelengths, such as may be the case for soils and some rock materials. Dark red is typical of trees and thick shrubs; light red associates with grass cover (also, early leafing or even certain plant disease). BACK


I-18: This is an example of what I call a "subjective" question in which no specific answer can easily be given owing to the particular choices of feature, location, etc. Hereafter, I will treat similar questions and their answers with the simple statement: Subjective. However, the red tones in the f.c. composite in this scene are medium gray in the bottom black and white photo but dark in the other two. BACK


I-19: 13,300 sq. miles; 33,225 sq. km; 8,512,000 acres. BACK


I-20: The detectors are electronic in nature and tend to respond similarly to each other when any particular number of photons strike each (over the same time). But, they are not exactly matched. So, when several scan lines cross the same ground feature (assume spectral homogeneity), they may have slightly different responses, causing in the images a distinguishable variation in gray level from one to the next. This helps to single out individual scan lines. Sometimes also, a given detector will experience a fluctuation in response from its normal mode, so that the line can be notably lighter or darker in its overall feature variations than its neighboring two lines. Computer processing can minimize differences, so that properly processed images seem almost free of individual lines.(red is spectrally farther from blue than from green).


I-21: Subjective. But, at the least you should have found Trenton, New Jersey.


I-22: Band 4 is rather "washed out" in that it shows an overall darkest tone with little contrast. But, it best shows the silt in the ocean waters. Band 5 shows the sharpest contrast (greatest spread of gray levels). Vegetation appears in the darkest gray tones. These tones emphasize the ridges in the upper left of this band image. In both 4 and 5, the Pine Barrens are somewhat darker; this speaks to the presence of considerable evergreen vegetation, with its darker needles. Band 6 is dominated by light tones, indicating that highly reflective vegetation is widespread. The dark patches are urban areas. Water in this Band, and 7, is extremely dark, as expected from its reflectances near zero. Band 7 is marked by even lighter tones. Both 6 and 7 show the Barrens to be a bit darker, suggesting that evergreens are somewhat less reflective than deciduous trees. Note that the ridges can be discerned even though they have little contrast with the vegetation-rich valleys in between. Also note that the cities don't stand out in Bands 4 and 5.


I-23: Subjective. You should have found the table's criteria to work fairly well.


I-24: For full scenes printed at a scale of 1:1,000,000 (the standard product, about 10 inches on a side, with white margins), the TM and MSS products show strong similarities, even in the details. This is because the effects of the added pixels (representing areas on the ground) at 30 meters do not appear sharply different in the TM images when compared with the 79 meters of the MSS. For an image of this scale, which extends over 7 inches on a side, for the 79 meter case, the size of a pixel is 79/185000 x 7 = 0.003 inches (the 185000 refers to the ground equivalent length of 185 km for the scene). The 30 meter case gives a pixel size of 0.001 inches. The eye cannot clearly differentiate between these two sizes. Where the higher resolution TM image produces obvious improvement occurs when the scale is changed to larger sizes (1:250,000 produces a 28 inch wide full image), with the pixels remaining still small enough (0.004 inches) not to be distracting to the eye (but the 79 meter MSS would have pixels of 0.012 inches, so that pixels will be seen and give a tiny but disturbing blocky effect). Likewise, when a subscene (part of a full image) is produced from TM data, it also appears sharper when printed at some typical size (e.g., 10 inches).


I-25: Because individual materials that occur within a class (for example, several species of minerals within a mineral group) express their variations in composition as slight shifts in peaks and troughs within a spectral curve continuum, hyperspectral sensors are capable of not only being excellent in identifying the different groups but also can determine the identities of individual members of such groups.


I-26: The more obvious difference is the distortion in the shape of features that have a strong three-dimension expression, such as mountains. In Landsat images, the mountains near San Francisco appear "normal", that is, they have slopes on either side of the mountain crests that are similar in slope angles. But, in the radar image one slope side seems stretched out and the opposing slope appears shortened; this is a hallmark of radar imagery known as layover. A second difference relates to gray tonal levels. In radar, some features have tonal signatures quite unlike those in Landsat Visible-Near IR images, the causes of which are covered in Section 8. A good example is the San Francisco Airport, which in radar is quite black but would have various shades of gray in most Landsat bands.

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History of Remote Sensing: Examples of TM Imagery


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This page is devoted primarily to displays of some Landsat TM images in natural and false color (and one comparison with an earlier MSS image); each is described. Presentation of black and white individual TM band images is deferred until the first part of Section 1 in this Tutorial.


History of Remote Sensing: Examples of TM Imagery

Below are three examples of Landsat-4 TM imagery in color. We refrain here from displaying any of the individual black and white TM bands because Section 1 presents and examines excellent examples of these from a subscene of Morro Bay, California.

The first TM image is a late Fall, false color (TM bands 2, 3, 5 in blue, green, and red) rendition of mountain ranges in southeastern California and western Nevada. The large valley towards the left is Death Valley, with the Panamint Range to its left. The large range near the upper right is the Spring Mountains, whose reddish tones indicate vegetation (mixed evergreens and deciduous trees). The bottom of the image includes the north edge of the Mojave Desert.

False color TM image in the late Fall of mountain ranges in Southeastern California and Nevada.

I-24: Until you have gained familiarization by close inspection of TM full images, you may by inclined to think that they are not much better than corresponding MSS images. Ponder that; why? For what image situation(s) will the improved resolution really make a difference. ANSWER

The second scene is an 80 km (50 mile) enlargement of part of a TM image covering the Sonoran Desert of northwest Mexico (a bit of the Gulf of California appears in the lower left), shown here in true color. Star and crescentic sand dunes dominate this subscene in this vast sand sea deposited over igneous lavas. The dark patches in the upper right are volcanic lavas but the dark mass to its southwest is the Sierra del Rosario, composed of granitic rocks.

A TM subscene in natural color of a portion of the Sonoran Desert in northwest Mexico (NE of the northern terminus of the Gulf of California) in which sand dunes and igneous rock units are the principal features.

The third TM image is also a subscene, about 70 km (43 miles) on a side, in west-central Mexico. Mexico City, with the largest urban population in the western hemisphere (about 30 million), appears in this false color version as the medium blue area in the upper left part of the image. Note that its area is much less than that of Los Angeles (one of the opening scenes in Section 4), indicating a high population density, i.e., crowding. The city lies at an average elevation of 2800 meters (9184 feet) astride the Neo-Volcanic Plateau, a zone that runs across Mexico and is seismically active. Just off the image to the right is a cluster of active volcanoes including the famed Popocatepetl which is over 5100 meters (almost 17000 feet).

TM false color subscene of part of west-central Mexico in which Mexico City (large lighter blue area in top-central) and some volcanoes are shown.

For comparison, we reproduce below a subscene imaged in 1973 by the first Landsat MSS. The area shown occupies about 2/3rds of the TM scene, pinned to the upper right corner. Draw your own conclusion about the relative details seen in the TM versus the MSS. Note that the size of Mexico City was not much smaller then even though its population was just over 7.5 million. The two images, when compared, illustrate the concept of change detection.

Landsat-1 MSS subscene, taken about 11 years earlier,  of the same general area of west-central Mexico shown in the TM scene just above. Mexico City in light blue (upper left) is somewhat smaller in area compared with the later subscene; this is another example of change detection. Also, the brighter reds indicate the MSS to be a summer image whereas the darker expression for equivalent areas in the TM subscene suggest it to be a winter view.

A Landsat-4 TM subscene shows the Cape Canaveral area of the east-central coast, where NASA's Kennedy Space Center (KSC) is located. Note the many individual launch sites. Compare this image with the RBV image of the same location shown near the bottom of page I-2-15.

A Landsat TM subscene in quasi-natural color that pinpoints many of the buildings and launch facilities at NASA�s Kennedy Space Center. The Banana (right) and Indian (left) inlets are visible as is part of Titusville on the mainland.

 A Landsat TM subscene in quasi-natural color that pinpoints many of the buildings and launch facilities at NASA�s Kennedy Space Center. The Banana (right) and Indian (left) inlets are visible as is part of Titusville on the mainland.

Landsat 7 has come on line in April of 1999 after its last working predecessor, Landsat 5 (remember, Landsat 6 failed to orbit), has continued to operate faithfully for 15 years (since 1984). Landsat 7 has only a single instrument, called the Enhanced Thematic Mapper (ETM+). A cutaway diagram of this instrument appears below:

The ETM+ sensor.
From A History of Civil Land Imaging Satellites, by Wm.Stoney
Encyclopedia of Space Science and Technology, J. Wiley & Sons.

The instrument consists of the same 6 bands in the Visible and Near Infrared as the TMs, again at 30 m resolution. The thermal band has an increase in spatial resolution by a factor of 2 - to 60 meters. The new component is a panchromatic (0.52 to 0.90 µm) black and white sensor (somewhat analogous to the RBV) which images at a 15 meter spatial resolution. The Landsat 7 program is operated jointed by NASA Goddard Space Flight Center and the U.S. Geological Survey. Here are some representative scenes.

The first scene acquired by Landsat 7 covers a part of southeastern South Dakota that includes the city of Sioux Falls. The U.S. Geological Survey's EROS Data Center (EDC), where Landsat imagery can be inspected and ordered, lies just off the image to the right.

A near-full (left and right edge sections cropped) ETM scene covering part of southeast South Dakota; this is the first scene acquired by this sensor on Landsat-7.

Part of the Landsat 7 panchromatic image of this same scene, showing a portion of Sioux Falls, with individual buildings now resolvable, is presented next.

Enlargement of an image acquired by the panchromatic sensor on Landsat-7 in which the northwest area in and around Sioux Falls, S.D. is displayed at 10 meter resolution.

Full Landsat scenes are commonly shown in their orbital slant mode set against a black background. Here is the Kaiseb River in Namibia, and a dune field to its south.

Landsat-7 full scene of part of Namibia along the west coast in southern Africa.

Another urban area is seen in this quasi-natural color Landsat 7 subscene of the "Peninsula" area south of San Francisco. At the top is the San Mateo Bridge and Foster City (just beneath its west terminus), a residential area built on extensive fill into the San Francisco Bay, thus on newly created land. The Dumbarton Bridge near the bottom right leads into Palo Alto, home of Stanford University. Note the salt pans to the left of the bridge. The lake - actually the Upper Crystal Springs Reservoir - near the bottom left lies right on top of the infamous San Andreas Fault Zone. The nearby road (a 100 feet or so higher) is Interstate 280.

A Landsat TM subscene produced in quasi-natural color showing some of the southern part of San Francisco Bay and areas in the Peninsula region that include the towns of San Mateo, Redwood City, and Menlo Park.

Goddard maintains a Landsat web site that now features a selected group of Landsat 7 images. Other information on Landsat 7 is included in the site established by the U..S. Geological Survey.

For those interested in the history of the Landsat program, click on this 11 page summary : http://geo.arc.nasa.gov/sge/landsat/lpchron.html. This Chronology was prepared for NASA at its Ames Research Center. They also maintain a general information bulletin board on Landsat (which includes the above historical perspective) that you can access at http://geo.arc.nasa.gov/sge/landsat/landsat.html. And for those curious about Landsat's future, read the paragraph that considers this on page 20-1, located just before the "Some Future Thoughts" subsection.


History of Remote Sensing: Landsat's Thematic Mapper (TM)


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A new 7 spectral band scanner, called the Thematic Mapper, was/is the prime instrument on Landsats 4, 5, and 6. This improved sensor system includes a blue band so that quasi-natural color images can be made, two bands in the mid-IR, and a thermal band. System resolution is increased to 30 meters. Landsat 7 carried a single sensor, the ETM+, which, besides the 7 bands, also has a panchromatic band that achieves 15 m resolution. The ability of the TM to better identify materials and classes is demonstrated.


History of Remote Sensing: Landsat's Thematic Mapper (TM)


A more sophistical multispectral imaging sensor, named the Thematic Mapper (TM) has been added to Landsats 4 (1982), 5 (1984), and 6 (this last failed to attain orbit during launch and thus has never returned data) and a modified version to Landsat-7 (1999). These TMs flew on redesigned, more advanced platforms, the first of which, Landsat-4, is pictured below:

Artist's painting of Landsat-4 (D) showing the locations of the MSS and TM sensors and other components.

Although similar in operational modes to the MSS (which was also part of the Landsat 4 and 5 payloads, to maintain continuity), the TM consists of 7 bands that have these characteristics:

Band No. Wavelength
Interval (µm)
Spectral
Response
Resolution (m)




1 0.45 - 0.52 Blue-Green 30
2 0.52 - 0.60 Green 30
3 0.63 - 0.69 Red 30
4 0.76 - 0.90 Near IR 30
5 1.55 - 1.75 Mid-IR 30
6 10.40 - 12.50 Thermal IR 120
7 2.08 - 2.35 Mid-IR 30

Six reflectance bands obtain their effective resolution at a nominal orbital altitude of 705 km (438 miles) through an IFOV of 0.043 mrad. The seventh band (but designated as Band 6) is the thermal channel, which has an IFOV of 0.172 mrad, which reduces resolution.

This diagram shows the placement of each band on a wavelength base:

Location of each TM band in terms of its spectral interval.

The TM spacecraft differs from the earlier MSS Landsats in the orbital repeat cycles, as shown in this diagram:

Comparison between Landsats 4 and 5 and 1, 2,and 3 in terms of orbital path repeat cycles.

Note that for the first three Landsats there is an 18 day swath cycle in which the shift to the west (left) is systematic in that Path 1 is reoccupied after the 251 orbits have been occupied over an 18 day period. But keep in mind that for each day there are 14 circumglobal orbits (each orbit taking 103 minutes) such that as the Earth turns below each next path will have shifted less (160 km) than one frame (full size = 185 km) width to the west, allowing for some (variable) overlap between successive frames. During the 14 cycle single day history the total western shift produces a continuous combined swath width of 14 x 160 = 2240 km (1400 miles). In the full 18 day cycle this leads to a total composite coverage of (40900 km) 25200 miles. Landsats 4 and 5, at a lower altitude (which helps in improving resolution), accomplish 233 orbits in 16 days. The repeat pattern is notably different, as shown by the variable offset lines in the upper map.

Here is a photograph of the Thematic Mapper on the ground before it was mated to the spacecraft. Note the gold leaf that is used to shield the inner workings.

Photograph of the Thematic Mapper.

This cutaway diagram shows the major components of the TM system. Not shown are the interference filters used to separate the radiation into spectral bands:

The Thematic Mapper system.

The sketch below shows some of the components in the optical train and detector layout of the TM.

Generalized layout of parts of the optical and detector components on the Thematic Mapper.

Instead of the 24 detectors on the MSS, the TM has a total of 96 for the reflective bands (16 each for a band; the mirror scan produces 16 lines at once) and 4 for the thermal band. For Bands 1-4, silicon metal is the photoelectric detector; for 5 and 7 an indium antimony (InSb) alloy is used; for Band 6, the detector is a mercury cadmium telluride alloy (HgCdTe). At any given IFOV, each detector views a slightly different part of the ground that will be represented in the pixel being activated by radiation at any instant. The radiation collected for each band passes through a scan line corrector which compensates for the forward motion of the spacecraft. Radiation comprising Bands 1 through 4 is sensed by silicon detectors located in one focal plane; Bands 5 and 7, in the Mid IR (SWIR) use InSb detectors and Band 6 used a HgCdTe detector. Radiation from all three band sets are focused on a second focal plane at the detectors; the spectral filters are just before the detector plane. Bands 5, 6, and 7 are subjected to a radiative cooling system to improve sensitivity. This figure summarizes the detector array layout for the Landsat ETM+:

The detector array arrangement for the Landsat EYM+, whose Band 8 is a panchromatic imager.

The TM's primary scan mirror takes imagery during both its left and its right swings (a full cycle; swing rate: there are 7 cycles/second). This results in a zig-zag pattern, in part because of the small but steady rotation of the Earth's surface below, as shown in the next figure. When the scan data are processed to produce an image, the lines are made to be parallel by using data acquired by two secondary mirrors (in parallel to one another; each rotating completely):

Scan line correction.

To introduce you to the differences in a TM image shown in all seven bands, we take a quick look at a scene in Florida:

A small area in Florida imaged by all 7 bands on the Landsat Thematic Mapper.

This table indicates the principal identification tasks that each band is especially adept at doing:

Specific utility of each band for class identification.

In more detail: Band 1 is superior to the MSS band 4 in detecting some features in water. It also allows us to form quasi-natural color composites. Band 5 is sensitive to variations in water content, both in leafy vegetation and as soil moisture. It also distinguishes between clouds (appearing dark) and bright snow (light). This band also responds to variations in ferric iron (Fe2 O3) content in rocks and soils, which show higher reflectances as the iron content increases. Band 7 likewise reacts to moisture contents and is especially suited to detecting hydrous minerals (such as clays or certain alteration products) in geologic settings. Band 6 can distinguish a radiant temperature difference of about 0.6° C and is helpful in discriminating rock types whose thermal properties show differences in temperatures near their surface. It often can pick out changes in ground temperatures due to moisture variation and can single out vegetation due to its evaporative cooling effect. The higher resolution achieved in the reflective bands is a significant aid in picking out features and classes whose minimum dimension is usually on the order of 30 m (98 ft) . Thus, it can often discern houses and smaller buildings, which were unresolvable in MSS images.

The size and shape of full TM images from Landsats 4 and 5 are identical to the MSS images. At first glance, the quality and characteristics of these full scene TM images seem similar to those made by the MSS after optimal computer-based processing, but on closer inspection they do appear sharper. This apparent similarity is due to the need to resample the TM images for TV monitor displays (which are not high resolution systems capable of reproducing all TM pixels) by dropping some pixels. The influence of the better TM resolution (when un-resampled) becomes apparent whenever photographs of full scenes are enlarged (pictures more than a meter on a side can be produced with exceptional clarity) or subscenes are extracted and enlarged. Also, higher resolution improves scene feature classification since many objects on the Earth's surface are smaller than 30 meters; thus computer-based classification should result in higher accuracies for individual class identification and location.


Best MSS Bands for Identifying Surface Features

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Best MSS Bands for Identifying Surface Features


Item Category Best Bands Salient Characteristics
a. Clear Water 7 Black tone in black and white and color.
b. Silty Water 4,7 Dark in 7; bluish in color.
c. Nonforested Coastal Wetlands 7 Dark gray tone between black water and light gray land; blocky pinks, reds, blues, blacks.
d. Deciduous Forests 5,7 Very dark tone in 5, light in 7; dark red.
e. Coniferous Forest 5,7 Mottled medium to dark gray in 7, very dark in 5; brownish-red and subdued tone in color,
f. Defoliated Forest 5,7 Lighter tone in 5, darker in 7 and grayish to brownish-red in color, relative to normal vegetation.
g. Mixed Forest 4,7 Combination of blotchy gray tones; mottled pinks, reds, and brownish-red.
h. Grasslands (in growth) 5,7 Light tone in black and white; pinkish-red.
i. Croplands and Pasture 5,7 Medium gray in 5, light in 7, pinkish to moderate red in color depending on growth stage.
j. Moist Ground 7 Irregular darker gray tones (broad);darker colors.
k. Soils-bare Rock-Fallow Fields 4,5,7 Depends on surface composition and extent of vegetative cover. If barren or exposed, may be brighter in 4 and 5 than in 7, Red soils and red rock in shades of yellow; gray soil and rock dark bluish; rock outcrops associated with large land forms and structure.
1. Faults and Fractures 5,7 Linear (straight to curved), often discontinuous; interrupts topography; sometimes vegetated.
m. Sand and Beaches 4,5 Bright in all bands; white, bluish, to light buff.
n. Stripped Land-Pits and Quarries 4,5 Similar to beaches – usually not near large water bodies; often mottled, depending on reclamation.
o. Urban Areas: Commercial Industrial 5,7 Usually light toned in 5, dark in 7, mottled bluish-gray with whitish and reddish specks.
p. Urban Areas: Residential 5,7 Mottled gray, with street patterns visible; pinkish to reddish.
q. Transportation 5,7 Linear patterns, dirt and concrete roads light, in 5; asphalt dark in 7.


History of Remote Sensing: MSS Histograms


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The Landsat MSS gathers radiation over spectral band widths that integrate radiation over relatively broad intervals (0.1 and 0.3 µm). Thus, instead of the spectral signatures that continuously measure spectral response in very narrow intervals, the MSS data when plotted produce histogram-like bars that are rough approximations of the signature curves. For different classes, these still yield separable patterns that facilitate identification of the materials involved. This is illustrated for a scene in central California. A table is included (by link) that specifies relative black and white gray levels and distinctive colors by which some common materials can be identified.


History of Remote Sensing: MSS Histograms

The MSS can simulate rather crude spectral signatures. Bands 4, 5, and 6 each have a bandwidth of 0.1 µm; and band 7's width is 0.3 µm. We represent band responses by bars in a histogram-like plot, in which the height of the bar signifies the relative reflectances averaged for all wavelengths within the bandwidth interval. Several crude spectral signatures (as bar histograms) are shown here, as derived from this Landsat image of a section of the U.S. West Coast.

This Landsat-1 image of central California contains common classes whose spectral responses as measured by the MSS consist of 4 bars (representing the 4 MSS bands) whose relative heights depict differences in reflectance. Note the similarities of the several vegetation types and the somewhat similar water and urban classes.

The scene is the first color composite made from ERTS-1 digital data. This includes Monterey Bay (lower left corner), the Coast Ranges below San Francisco, the Sacramento (Great) Valley, and the western slopes of the Sierra Nevada. Notice that the pattern of each histogram set, for a particular type of surface cover, differs from the others. Thus, each class of material has a distinctive signature, roughly approximated by the 4 bars, that sets it apart. To simplify the plot, we made the width of band 7 (bar on the right) equal to the other three. Urban is most reflective in bands 4 and 5; suburban is strong in bands 4 and 7 (the latter is tied to the influence of live vegetation in lawn grass and landscaping trees). The signatures for forest and healthy croplands are similar, but the heights of the bars for bands 6 and 7 are greater for the crops. The bar heights for small grains and fallow fields are similar, but the response for bands 4 and 5 is just a bit higher than for 6 and 7. The two very dark areas in the Coast Range and in the Sierra Nevada (not shown as histograms) result from the predominance of conifers.

Next, refer to the table on the next page in which we present some criteria for using combinations of band gray tones or colors and their patterns to identify land-cover categories. Most categories are described by their MSS Bands 5 and 7, and sometimes 4, response. Again, apply these to recognize examples of any such categories in the California scene. Become familiar with this table, because we challenge you to practice this approach whenever you examine various Landsat scenes (and imagery from the other earth-observing satellites) in this Tutorial.

I-23: Print out this table; it will serve as a handy reference for other scenes in this Tutorial. Scroll back to both the New Jersey and California scenes above and apply the table criteria (gray levels; color) to features/classes you have identified earlier to ascertain the validity of these criteria. ANSWER


History of Remote Sensing: A Landsat Image


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Here we consider how the 4 Landsat MSS bands produce multispectral images of the same area in the eastern U.S. (which you are asked to identify before reading a detailed description of its geography) as scanned in October 1972. These images are displayed side by side and then beneath them is a false color composite of the same area plus a bit more to the south. The idea behind change detection is introduced by looking at a MSS Band 7 image of the area obtained in April 1978 (Spring) and comparing it with the Fall �72 Band 7 image.


History of Remote Sensing: A Landsat Image

The picture below is a Landsat full image, from October 1972, shown both as individual bands and as a false color composite. We display below a succession of MSS bands 4 through 7 (bands 1-3 were assigned to the RBV), comprising images of a very well known region in the eastern U.S. Beneath these four images, is a false color composite, made from bands 4, 5, and 7, of this scene, here extended southward to include the southern tip of a peninsula that includes the town of Cape May (a clue).

Note 1: By convention, Landsat and most other satellite system images are normally oriented with North towards the top. However, because of the ninety-nine degree orbital inclination, the north direction is not vertical but is a few degrees inclined relative to the perpendicular to the top and bottom margins of the printed image.

Note 2: The lettering at the bottom of each image (probably not readable on your screen) is the standard annotation placed on Landsat images produced at NASA, EROS, and most commercial facilities. The information recorded, from left to right, includes the calendar date of acquisition, the latitude-longitude coordinates of the scene principal and nadir points, the sensor type, the elevation and azimuth positions of the Sun, and the Scene (Frame) identification number (I.D.) starting with the particular Landsat (1 through 5) and ending with the specific band (or band combination if in color).

Before you look at the second paragraph beneath this image set, we challenge you to try to identify what geographic area is shown here.

Landsat MSS October 10, 1972
Landsat image of New Jersey and New York City (October 10, 1972) - MSS Band 4

MSS Band 4

Landsat image of New Jersey and New York City (October 10, 1972) - MSS Band 5

MSS Band 5

Landsat image of New Jersey and New York City (October 10, 1972) - MSS Band 6

MSS Band 6

Landsat image of New Jersey and New York City (October 10, 1972) - MSS Band 7

MSS Band 7


These bands plus a small part of the next image to the south joined (mosaicked) to them can be combined to make a standard false color composite using the three Band combinations as shown below the image:

False Color composite made from bands 4 (blue), 5 (green) and 7 (red) above, for the October 10 New York/New Jersey scene plus an extension down to Cape May, NJ

MSS Band 4 = Blue

MSS Band 5 = Green

MSS Band 7 = Red

If you correctly identified the scene, then in the individual bands, you saw much of New Jersey along with New York City and the west end of Long Island in the upper right corner and Philadelphia at just left of the image center. The color composite extends the coverage to the northern Delmarva Peninsula, flanked by the northern Chesapeake Bay (bottom left) and Delaware Bay (bottom center) and Cape May (bottom right). These two urban regions, along New Jersey cities along the Hudson River, appear in light to medium gray-blue tones in Band 5 (red). In Band 7 (IR), the central areas of these metropolitan complexes are in dark tones, owing largely to the prevalence of asphalt streets and dark (usually asphalt) roofs, together with few trees and little other vegetation. In Bands 6 and 7, the urban scene contrasts with the lighter tones associated with high reflectance vegetation in the countryside. Water is dark in Bands 6 and 7 but lighter in Bands 4 and 5, in part because of silt and other sediments (more reflective). In contrast, among the brightest features in both individual-band and color composite scenes are the sandy beaches and soils comprising the ocean side of the barrier islands lining the New Jersey coast.

Vegetation in this October 10, 1972 scene is still actively growing (mostly green in natural color, but some trees are beginning to get their autumn colors), so its spectral distribution indicates an overall brightness in the Band 6 and 7 images. We can compare the dark tones of the fold belt ridges in the upper left in Band 5 with their corresponding light tones (from high reflectances related to tree leaves; this ridges are heavily forested) in Band 7. Surfaces dominated by vegetation are shown in several shades of red in the false color composite. Harvested (fallow) fields appear in blue tones, similar to those characterizing the cities. The large, darker area in New Jersey east of Philadelphia is the Pine Barrens, marked by evergreens that grow well in the sandy soils (Note the appearance of these trees in each of the four bands; in color, they are reddish brown; evergreens are bright but not as much as deciduous trees).

I-21: Try your hand at picking out other major landmarks in the scene (use an atlas for help in recognizing their locations). ANSWER

I-22: Although it may be a "pain" scrolling up and down repeatedly, we suggest you pick out various features in each of the four MSS band images and note how they appear, in terms of gray levels (and shapes) in each band; in other words, compare. Also, describe the overall appearance of each band relative to the others. Do this mentally, or write it down if you wish. This is a worthwhile task, as it will give you a "feel" for the general nature of each of the four bands that represent the continuum of spectral intervals from 0.4 to 1.1 µm. ANSWER

As a preview of change detection, compare the October 1972, Band 7 image above with the one below, which was taken on April 18, 1978. Because it's a time in the Spring in which trees and other vegetation in the eastern U.S. have not yet leafed out there are especially dark ridges whose tones result from low rock and soil reflectances that dominate the radiances because of the absence of leaves). This seasonal effect results in a reduction in brightness over much of the areas in the lowlands where the fields remain fallow prior to emergence of growing vegetation. Many of the brighter areas in this April image do correlate with some field crops that were planted earlier; small bright patches in the Pine Barrens are sand pits - highly reflective in all bands.

Landsat image of New Jersey and New York City (April 18, 1978) - MSS Band 7

Of course, picking up changes over large areas and long time spans is just one of many uses that space imagery is being put to. Another common use is land cover/land use assessment, in which the identifiable features and classes on the ground are classified by techniques to be described in Section 1. As an example here is a classification of major ground cover types in part of one county (Monmouth) in New Jersey just south of Sandy Hook. Its specific purpose was to define the surface characteristics that could affect water quality planning in the Navesink Watershed. This map was made using Landsat MSS imagery.

Land cover classification of the Navesink Watershed in Monmouth County, New Jersey.

The reader may have noticed that in the two black and white Landsat-1 images near the top of this page there is a gray bar and some annotation on the bottom. This is a common format used in most renditions of early Landsat images and in some more recent versions. (Throughout the Tutorial this information is usually cropped off to reduce image size; it is almost unreadable on Internet pages anyway). We show another image (North Africa) here which contains all normally peripheral information included in photo prints of Landsat imagery:

A full-sized Landsat-1 image containing gray bars (top & bottom) and annotation; the region shown is in North Africa and shows large igneous plutons (dark).

The annotation contains valuable information. Here is an enlargement of the annotation in the above image:

Annotation and gray bar extracted from the African image.

The first writing on the very left of the annotation row is the date of scene acquisition. This is followed by two groups of letters/numbers that define: a. the latitude-longitude coordinates of the principal point (format center), then b. latitude-longitude coordinates of scene nadir point (nadir refers to a line from the platform vertical to the ground). Next to the right is the identification of sensor (MSS) and Band (7). Then comes the elevation of the Sun (angle above horizon) and the Sun's location (azimuth defining Sun's position above the horizon geographically relative to true North), both at the time of scene acquisition. The next string of alphanumerics contains specialized information including spacecraft heading (189°), then (G), location of the receiving station (here, Goldstone in California), followed by I-N-D-IL for I = full size, N = normal processing, D = definitive accuracy for image center, 1L = 1 for linear mode for spacecraft data transmission (2 would be compressed mode), and L for low gain (H would be high gain) signal amplification level. NASA ERTS signifies that this product was made by NASA's ERTS (Landsat) satellite. The farthest right alphanumerics, E-1106-09183-7 specifies ERTS (E) followed by the mission number (1 for ERTS-1), plus 106 for the number of days after launch, -09183, the hour (09), minute (18), and second (7), all local time of observation (for scene center). The last, 01, is known as the regeneration number. Below the gray bar are three numbers that mark the longitudes (here E = east of Greenich, London) in degrees and minutes as these intersect the bottom of the image frame; these numbers appear at the top again, shifted left because of the orbital inclination.

In ordering Landsat imagery, information in the annotation can be helpful. There is another aid that users often use instead. For the Landsat program, the Worldwide Reference System (WRS) was established. This is a grid with near up and down lines called the Path trace and horizontal lines the Row coordinates. We show this map of the coordinate system, realizing that on the Internet, the numbers and words appear too small to be readable:

The master map for the WRS-2 coordinates.

Look at a small part of the Path-Row system that crosses this map:

Path-Row coordinates for a Landsat scene in Ohio.

For Landsats 1-3, there are 251 Paths (001 to 251), the same number of orbits needed by these spacecraft to image the Earth in one 18-day cycle. There are 120 Rows, with 1 starting near the North Pole (80°47'), 60 coinciding with the Equator, and 120 in high south polar latitude. Path 001 is set at an equatorial crossing point of 64°36'

WRS-1 refers to the coordinate set used for the first three Landsat. WRS-2 denotes use by Landsats 4, 5, and 7. Because of the lower orbital altitude, this map contains 233 Paths. When the above Ohio scene is ordered, its location can be specified as Path = 19, Row = 31. Then a time-of-year date is selected, and, usually, a limit (in percent) of cloud cover (anything below that is acceptable).