We turn now to lineaments. In the early days of Landsat, perhaps the most commonly cited use of space imagery in Geology was to detect linear features that showed up as tonal discontinuities. Almost anything that appeared as a roughly straight line in an image was suspected to be geological in nature. Most such lineaments were attributed either to faulting or to fracture systems that were controlled by joints (fractures without relative offsets). Lineaments are well-known phenomena in the Earth's crust. Rocks exposed as surfaces or in road cuts or stream outcrops typically show innumerable fractures in different orientations, commonly spaced fractions of a meter to a few meters apart. These tend to die out locally as individuals but fracture trends persist. The orientations are often systematic in that in a region or a locale joint planes are apt to lie in spatial positions having several limited directions relative to north and relative to horizontal (for example, 60% might fall into a cluster of fractures having azimuths between N40W and N60W and inclinations between 30 and 40 degrees).

Where continuous subsurface fracture planes in sets that extend over large distances intersect the land surface, they produce linear traces (lineaments). Linear features in general can show up in aerial photos or space images either as a discontinuity that is darker (lighter) than lighter (darker) surfaces on either side; or, one side can be light, the other dark. Obviously, some such features are not geological in nature: these could be fence lines between fields of different crops or roads or variations in land use. Others may be geo-topographical: ridge crests, set off by shadowing. But those that are structural - joints and faults - are made visible in several ways. They commonly are opened up and enlarged by erosion. Some may even become small valleys. Being zones of weakness, they may be scoured out by glacial action and many of these depressions are then filled by water to become elongate lakes (the Great Lakes are the prime example). Ground water may invade the fragmented rock and gouge that mark faults or seep into the joints, causing periodic dampness that can be detected optically, thermally, or by radar. Vegetation can then develop in this moisture-rich soil, so that at certain times of year linear features are enhanced. All of these conditions can be detected in aerial or space imagery.

When a space image, particularly as a transparency, is properly illuminated, as on a light table, the viewer often spots numerous linear or boundary discontinuities that he/she might record on an overlying tracing paper. The resulting lineaments map may be covered with dozens, even hundreds of straight to curved lines that can be very impressive. But, scientific skepticism can raise sobering questions: Are they real? Do they all correspond to the same feature or phenomenon? If not, what is the proper identity of each one? And, finally, how does one go about verifying their existence and determining their identities? These are important issues since lineaments (particularly those that prove to be faults) are known to play key roles in localization of minerals and some oil/gas deposits and may give clues relevant to structural activities that may bear on earthquakes. We will save responses to these questions until the end of this section, after you have familiarized yourself with the appearance of lineaments in images. Near the end of Section 5, we will again consider the effects of human operator variations on the correctness and consistency in picking out valid lineaments midst "phony" lines.

The very first practical use of ERTS-1 (Landsat-1) imagery in any discipline was the drawing by Dr. Paul D. Lowman, Jr, a geologist at Goddard Space Flight Center, and an expert on space photography (he prepared Section 12 on Astronaut Imagery in this Tutorial), of a geologic structures map on the inaugural color composite image, of the central California coast around Monterey Bay, acquired 3 days after launch. This map confirmed

predictions from his studies of astronaut photos that Landsat would be an efficient tool for recognizing faults and other known structural trends in small-scale imagery that, despite lower resolutions than photographs, excels in portraying a regional geologic setting and has the advantage of being easily modified by digital processing. Within a month of this launch, images of the central Rocky Mountains were delivered to members of a team of investigators at the University of Wyoming. Professor Ronald Parker, a structural geologist, had been field mapping lineaments and other deformation features in the Wind River Mountains in the west-central part of the state. This great block of metamorphic and igneous basement rocks, flanked and patchily-covered by Paleozoic sedimentary rocks, is part of a segment of the Rockies where sections of the crust had been uplifted 6 km or more above other segments that stayed put or had downdropped to form deep (up to 6 km below present surface) basins now back-filled by erosional debris from the several surrounding mountain groups. As seen here by Landsat, the Wind River Mountains (center right) lie between the Wind River Basin (upper) and Green River Basin (lower), with the Gros Ventre and Hoback Ranges to the west. The Wind River Mountains rise to more than 3940 m (13,000 feet) above sealevel and have been strongly dissected by river and glacial action that has exposed and carved out many major faults and lineaments.Most can be easily mapped in the field or from the limited aerial photo coverage. As part of the project, NASA had previously flown a U-2 across a single pathway, picturing terrains like this: This photo shows an eroded granitic surface in which numerous lineaments are exposed.

Dr. Parker over 5 field seasons (camping in the high country; supported by pack mules) had completed ground mapping of faults, shear zones, and filled dikes in about 20% of the Wind River uplifted block, supplemented by photointerpretation of the U-2 strip, as shown in this left map:

Upon receipt of a Band 5 Landsat (ERTS) image, Parker produced this lineaments map on the right in just 3 hours (including a coffee break). Some of the newly plotted lineaments had been discovered earlier by other geologists, but most were heretofore unknown, and some of those have since been verified in the field. The telling point to this is: The synoptic overview of a large section of fractured continental crust could now be mapped with acceptable reliability in less than a day rather than months of difficult field work in poorly accessed terrain. This amounts to great savings in time and money. But, this mapping is of necessity incomplete and somewhat misleading. The maps below compare lineaments ERTS/Skylab Lineaments maps

from the central Wind River Mountains drawn on this ERTS image with those found in an astronaut photo taken from Skylab Mission S-190B. The orientation - azimuth or compass bearing of the dominant direction relative to north - of each linear feature can plotted in a rose diagram (at map bottom). This shows directions for all linear sets that have been grouped in intervals (here 10°) such that the length of the tapering bar in each interval is proportional to its frequency distribution (relative proportion) among all lineaments in the intervals distributed over the 180° that encompass west to east trends. Note that the dominant directions for ERTS lineaments are NE whereas those for Skylab are NNW.

The cause of this difference between the two observations is simply time of day. The ERTS image was acquired around 10:30 A.M. local time when the Sun's rays came from a SE position at a moderate elevation angle. Fractures occupying depressions that trend NE are subject to shadowing on their NW side - and hence would stand out in the image as shadow relief - whereas those trending NW would be equally illuminated on both sides - and hence largely invisible and easily missed. The Skylab photo was taken in mid-afternoon when the Sun was shining towards the NE at a higher elevation so that shadows would maximize along NW trending lineaments. This illumination bias is a well-known effect (see Section 11) and forces one to be cautious about conclusions dealing with structural trends when only data sets taken at one time of day are available. The obvious solution - multiple data sets obtained at different times - is not an option with Landsat (however, a geostationary satellite that can image at any time would circumvent this problem, but no high resolution systems [superior to meteorological ones] are as yet operational).

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