remote sensing At the roots of geology is the need to visualize how layers and irregular masses of rock relate to one another and extend into three dimensions, particularly where they are hidden from view beneath the surface. Geologists have traditionally pieced together such basic models by marking occurrences of different rock-types on topographic maps and then estimating how the outcrops link together on the land surface. Matching such a geological map with the shape of the land surface gives an idea of three-dimensional geology, which can be extended beneath the surface by using some simple geometry. All this requires much arduous, painstaking, and sometimes confusing work. Looking vertically downwards on a region from an aircraft or an orbiting satellite provides far more information about these geological attributes than one could ever hope to discover on the ground during a reconnaissance mapping programme.

Photogeology: image interpretation

Interpreting views from above speeds up and clarifies geological mapping, and adds otherwise inaccessible information to the generation of ideas about the disposition of rocks and to understanding some geological processes. That, in a nutshell, is what geological remote sensing is all about.

Downward-looking aerial photographs are the stock-in-trade of any kind of modern mapping. Aerial surveys entail taking photographs at intervals along a regular pattern of flight lines, so that every part of the surface appears on at least two frames in a sequence. The detail that appears on the photographs, even from high altitudes, is very fine, usually picking out objects a metre or less across. Equally important, in a similar fashion to the way in which our left and right eyes each record a slightly different view of the scene before us, and thereby allow us to perceive the world in three dimensions, successive aerial photographs incorporate this parallax shift because of the lens geometry and the position of each exposure. Whereas our eyes are about 7.5 centimetres apart, the separation between adjacent aerial photographs is at least several hundred metres. A viewing device called a stereoscope presents the photographs to the left and right eyes, effectively increasing the eye separation to a ridiculous degree. Instead of being completely unable to judge relief by simply looking out of an aircraft at high altitude the result is an amazingly exaggerated stereoscopic impression of topography. Details of rock variation and structure in well-exposed terrain are seen in their full context, and relatively little geological knowledge and experience are needed to make a useful geological map.

Photographs are limited to a narrow range of the electromagnetic spectrum—the visible region and the infrared at slightly longer wavelengths than visible red—that has its origin in the Sun's radiation and is reflected to various degrees by the surface. Apart from a few rare types, even the most pristine rock surfaces appear to us as shades of grey, with tinges of yellows, reds, and browns that result from various amounts of iron oxides and hydroxides. Naturally weathered rock surfaces assume this limited range of colour, with some additional confusion caused by varying cover by lichens. Much of the land surface exposes no rock at all, and is dominated by soil blankets in arid areas and by vegetation where conditions are more humid. The visible range is therefore of little help in enabling different rocks to be discriminated from a distance to the degree that is possible for the field geologist. But a limited differentiation of lithologies is possible.

A photogeologist uses the different ways in which various rock-types respond to weathering and erosion under the prevailing climatic conditions to distinguish them. Some rocks that are compact and hard, such as many crystalline igneous and metamorphic rocks, and carbonates and some sandstones among the sedimentary rocks, resist being worn down, even by the action of glaciers. So they tend to form uplands, and ridges if they are stratified. Less resistant rocks, such as shales, some schists, and all poorly consolidated sediments, form lowlands and vales parallel to the regional strike. It is these ridges and vales formed by variably resistant, stratified rocks that provide the key information from which geological structure can be worked out. Dip slopes and scarps stand out very clearly on stereoscopic photographs and allow accurate estimation of dip angle and direction for strata, as well as the shape of folds. Given a dip direction in a sequence of stratified rocks, it is a simple matter to establish a stratigraphical sequence. Even on a single image the direction and amount of dip can be roughly estimated by using the ‘Law of Vs’ if the topography includes well-defined valleys and ridges. Faults usually weaken rocks by shattering them to some extent, and some linear valleys are controlled in this way, particularly if the faults assume a steep angle of dip. Careful scrutiny of photographs for truncations of strike and for repetition or omission of strata in a stratigraphical sequence is a means of detecting faults with gentle angles of dip and establishing their sense of movement.

Depending on several factors, of which permeability is the most important, different rocks tend to have variable densities of streams and rilles developed upon them. The shapes in cross-section of individual drainage patterns vary according to lithological differences in resistance to erosion on a variety of scales. These two factors control the topographic textures that develop on different rock-types. The disposition of drainages, interfluves, and ridges in an area contributes to a wide variety of patterns seen on images. Such organization of topography relates to a host of factors. Among these are the spacing of compositional banding and joints, the intensity of foliation, and the presence of landforms, such as volcanoes, associated with the original formation of a rock.

So, geological interpretation of aerial photographs, and those taken from space, depends mainly on assessing erosional resistance, textures, and patterns, as well as the limited differences in colour or grey-tone of rocks in the visible part of the spectrum. This simple ‘toolkit’ of interpretative methods forms a framework for the geological interpretation of all remotely sensed images, including these that are captured by non-photographic means and use non-visible radiation.

Modern developments

Since the late 1960s scientists have developed a range of solid-state detectors, akin to transistors and capacitors, that are sensitive to electromagnetic radiation extending well beyond the wavelengths of visible light. These make it possible to detect radiation that is emitted by the Earth as well as solar radiation reflected by surface materials. It is in the infrared region where minerals, plants, rocks, and soils exhibit their greatest differences. The spectral variability of natural materials has been known for a long time from laboratory studies. The new detectors, together with instruments that focus radiation from distant surfaces on them and developments in information compression, transmission, and storage, enable entirely new kinds of imagery to be produced and put to use.

Instead of using photosensitive material in a film emulsion to record ‘one-off’ images through a lens, the new devices employ optical–mechanical methods to build up images during the time it takes a platform—an aircraft or a satellite—to pass over an area. One method uses a back-and-forth sweeping mirror to direct radiation reflected or emitted from a narrow strip of ground beneath on to a detector for each of several ranges of wavelength (line scanners). Another sweeps long arrays of thousands of identical detectors tuned to such wavebands across the ground (pushbrooms). In a line scanner the continuously varying electronic response from the detectors is divided in equal time intervals into segments that correspond to small rectangular patches of the surface. At any instant the detectors in a pushbroom respond proportionally to radiation from patches along a line on the ground. Images are built up of thousands of these lines made up of picture elements (pixels) that represent the patches. To simplify recording and transmission, and also later processing, the signal for each pixel is converted to a digital number in the 0to 255 range encoded in binary notation. The image data no longer need a medium in order to be preserved; they are simply transmitted and recorded on magnetic tape. In this form countless copies can be made, and, more importantly, images can be manipulated by computer in many appropriate ways.

Pictures made up of mathematically perfect rectangular arrays of pixels can be reassembled on a video monitor—which itself uses pixels—and the many different wavebands collected at the same time are registered exactly with one another. The last point means that data from any three wavebands (and often more, in various mathematical combinations) can be used as the red, green, and blue controls for a video display, thereby producing a colour image. However, unless the bands correspond to the three divisions of visible radiation, the picture is a colour rendition of the completely invisible; a false-colour image. How this is composed depends on the objective of the investigator, for the spectra of materials reveal differences in many different wavelength regions.

The visible region of rock spectra is dominated by the main colouring agent in rocks, iron, in the form of oxides and hydroxides. These minerals, either in the matrix of sediments or in a weathering veneer, absorb more blue and green (0.4–0.6 micrometres (μm) than red (0.6–0.7μm) in sunlight (Fig. 1b); that is the reason for the dominant reds, oranges, yellows, and browns of most bare rock in arid regions. A natural-colour image therefore adds only the parameter of redness to overall reflectivity, texture, and pattern as ‘tools’ for discrimination of rock-types without the aid of a close-up view, a hammer, and a microscope. The influence of iron minerals extends a little way into the infrared, where processes at the molecular level produce a broad absorption around 0.9micrometres (μm).

Infrared imagery

In what is known as the short-wave infrared or SWIR, between 2.1 and 2.4 μm, the spectral possibilities become more promising. Molecular interactions with radiation that involves Al–OH, Mg–OH, and C–O bonds result in a number of narrow absorption features, the exact position of which depends on the specific mineral molecule (Fig. 1b). Measurements in this region can therefore be used to detect minerals such as micas, clays, and many magnesium-bearing silicates containing the OH⁻ radical, such as chlorite, talc, and serpentine, and carbonates, provided that the remotely sensed data are divided into narrow wavelength intervals. Whereas the SWIR region is the focus for much geological remote sensing, the spectral features involved are mainly governed by minerals produced by weathering, not by rock-forming minerals. Distinction between different rocks on this basis usually matches field division very well, but direct identification of rock-types, other than carbonates, is not achievable without field confirmation.

Beyond 2.4 μm, radiation from the Earth becomes dominated by that which is emitted by the surface because of its temperature, rather than by reflected solar energy. As in the SWIR, molecular processes govern the intricacies of thermal spectra, but in this case the dominant processes are those in rock-forming minerals, principally the silicates. Quartz, feldspars, micas, amphiboles, pyroxenes, and olivines have quite different thermal emission spectra; so remote sensing that measures energy emitted in several narrow thermal wavebands potentially provides a means of direct lithological mapping (Fig. 1a). Several factors, such as soil and vegetation cover, and technical problems temper the apparently revolutionary potential of thermal mapping in geology. Several instruments are, however now being deployed to test the possibilities and are planned to become part of the international Earth Observation programme aboard unmanned satellites (1998 onward).

Although vegetation is one of the curses sent to try geologists, differences in rock and soil on which plants grow subtly affect vegetation, either by encouraging the growth of different floras on different substrates or because underlying chemical factors affect the health of plants. In terms of reflection of solar radiation, plants are unique. As well as being green, because chlorophyll absorbs red and blue, plants have evolved a cellular mechanism that prevents them from overheating by reducing the amount of radiation that they absorb. This dominates their infrared spectra, where wavelengths beyond 0.75 μm are efficiently reflected away. The efficiency varies from species to species, and also depends on the health of the plant. Water molecules in plant cells also absorb radiation at wavelengths around 1.4 and 1.9 μm, and their moisture content can accordingly be assessed. Consequently, by imaging the visible and near-visible infrared it is possible to detect botanical variations and anomalies that are indirectly related to underlying geology. This provides a remote-sensing approach that can be particularly useful in exploration for minerals, hydrocarbon seepages, and water resources. The peculiar reflectance of infrared radiation by plants forms the main source of remotely sensed information about the biosphere on land.

Radar systems

In the microwave part of the electromagnetic (EM) spectrum (wavelength less than 1 mm) natural energy emissions are too low for useful remote sensing. Instead, imaging radar systems are used to illuminate the surface with artificial microwave energy, which can penetrate cloud cover. At such long wavelengths the interactions between radiation and the surface are dominated by the attitude of the surface in relation to the platform and by small-scale surface roughness (Fig. 1a). The information conveyed by radar images is consequently, very different from that obtained at shorter wavelengths. Radar is particularly good at showing up variations in surface texture that depend partly on the small-scale responses of rocks to weathering and erosional processes, and also on the nature of any vegetation canopy. Since radar images can be produced only by illumination from the side, large-scale features in the topography are exaggerated by highlighting and radar shadows. This makes radar images especially effective in outlining geological structures.

Digital image processing

As mentioned above, most modern remotely sensed images are in digital form, with energy levels expressed as arbitrary integers from 0 to 255 (1 byte) in binary code for each of millions of pixels. Digital image processing centres on information in this format. It employs a large and growing range of image transformations aimed at removing defects introduced by imaging instruments, registering images to map projections and map data, modifying or enhancing contrast, combining different kinds of data arithmetically, enhancing or suppressing spatial attributes in images, such as textures, patterns, and shapes, and extracting a wealth of statistical information from image data. The last forms the basis for automatic division of materials at the Earth's surface into different spectral classes. This is most often used in studying vegetation but is potentially useful in geological mapping.

As well as the information gathered in image form, Earth scientists now have access to other information on geographically varying properties of the Earth's surface and its interior, usually at isolated points or along survey lines. These data include topographic elevation, depths to rock boundaries, measures of magnetic and gravitational field strength, and the concentration of chemical elements in soils and stream sediments. By assuming that such isolated measurements are part of a natural continuum that can be represented mathematically by a three-dimensional surface, these data can be transformed into image form by interpolation. Although not remotely sensed in the strict sense, such representations can be enhanced and manipulated in exactly the same way as digital images. This opens up an enormous range of possibilities for comparing every aspect of the Earth's properties rapidly, conveniently, and in a common geographic context. In this way otherwise unachievable correlations and coincidences become visible, so that Earth scientists can use them in modelling natural processes. Such geographical information systems lend themselves to exploration for many physical and biological resources, and environmental management and monitoring, as well as for more academic pursuits.

S. A. Drury

Remote Sensing

█ WILLIAM C. HANEBERG

Remote sensing is the acquisition of information about an object or phenomenon by a device located a considerable distance from the object or phenomenon. The term was coined in the mid-1950s by an Office of Naval Research scientist to distinguish the information obtained from the first generation of meteorological satellites from that which had been traditionally obtained by airplane-based aerial photography. In practice, however, information obtained from high-flying reconnaissance aircraft such as the U-2 and SR-71 can also be considered to be a product of remote sensing.

In addition to providing panchromatic (black and white) and multispectral color images that resemble photographs, some modern remote sensing satellites contain hyperspectral sensors that record information using dozens or hundreds of reflected electromagnetic energy wavelength bands that extend beyond the range of human vision. The simplest kind of multispectral image consists of red, blue, and green bands added together to form a color composite image. Image processing software can be used, particularly with hyperspectral data, to identify the chemical composition of rocks, vegetation type, soil or

water pollution, and other attributes that can be characterized in terms of spectral reflectance. Paired images can also be used to stereoscopically construct digital elevation models (DEMs), which can subsequently be transformed into topographic maps or three dimensional terrain models from space.

Other satellites contain active sensors that generate their own electromagnetic signals and record the reflections rather than passively recording reflected natural radiation. Synthetic aperture radar (SAR), in particular, is a useful tool because it can penetrate clouds and be used at night. The length of a radar antenna is known as its aperture and, in general, the resolution of a radar image is proportional to antenna length. The term synthetic aperture refers to a technique in which the constant movement of a satellite is combined with periodic radar pulses and computer processing to achieve the same effect as would be obtained by using a very large antenna. Pairs of SAR images can be combined to produce interferometric (InSAR) images that portray millimeter to centimeter scale changes in the elevation of Earth's surface. InSAR is becoming an increasingly important tool for monitoring tectonic movements of Earth's crust, subsidence associated with heavy groundwater pumping, and other geologic processes. It can also be used to construct digital elevation models. Another active source remote sensing technique is light detection and ranging (LIDAR), which is similar to radar but uses a laser instead of radio waves to produce extremely detailed topographic maps and images.

It is generally understood that remote sensing satellites must have a resolution of 5 meters (m) or less to be useful for intelligence work. The Landsat 1 satellite, launched by the United States in 1972 and from which imagery was freely available, had a resolution of 80 m. Landsat 7, launched in 1999 and still in service, has resolutions of 15 m for panchromatic images, 30 m for its six multispectral bands, and 60 m for its thermal band. The French SPOT 5 satellite offers commercially available images ranging in resolution from 5 m for panchromatic to 20 m for infrared. Publicly available images with these coarse resolutions are useful for such tasks as delineating large-scale geologic features, evaluating inaccessible or denied terrain, examining land use patterns, and inferring levels of crop stress, but not for detailed intelligence work. In recent years, however, commercial remote sensing satellites have been able to obtain high-resolution images that are of intelligence quality. The commercial Quick Bird satellite launched from Vandenberg Air Force Base in late 2001, for example, provides commercially available imagery with 61 cm panchromatic and 2.44 m multispectral resolution. The commercial IKONOS satellite, launched in 1999, can produce 1 m resolution color images.

Even the best publicly available imagery does not approach the resolution provided by classified intelligence satellites. The earliest KeyHole intelligence satellites (KH1 series), the first of which was launched by the United States in 1960, had a resolution of 2 m. Photographic film from KeyHole satellites was recovered using film drops until 1972, when digital imaging and transmission were instituted. The KH12 series is estimated to have a resolution of approximately 2 cm, although no images with this resolution have been released. Intelligence-quality images with sub-meter resolution can be used to assess details of troop or materiel movement, the progress of construction projects, and war damage in denied or otherwise inaccessible areas. Perhaps the most widely known application of remotely sensed images for intelligence work was the use of satellite and U-2 airplane photographs to detect the presence of Russian missiles in Cuba, which led to the 1962 Cuban missile crisis.

█ FURTHER READING:

BOOKS:

Campbell, James B. Introduction to Remote Sensing, 3rd ed. New York: Guilford Press, 2002.

ELECTRONIC:

Hardin, R. Winn. "Remote Sensing Satellite Market Pits Industry Against U.S. Policy." OE Reports. May 1999. <http://www.spie.org/app/publications/magazines/oerarchive/may/may99/cover1.html> (November 14, 2002).

Short, Nicholas M., Sr. "The Remote Sensing Tutorial." NASA. October 22, 2002. <http://rst.gsfc.nasa.gov/> (November 14, 2002).

Skorve, Johnny E. "Using Satellite Imagery to Map Military Bases of the Former Soviet Union." Earth Observation Magazine. April 2002. <http://www.eomonline.com/Common/currentissues/Apr02/skorve.htm> (November 14, 2002).

International Society for Photogrammetry and Remote Sensing, Department of Geomatic Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom. 44 207679 7226. <http://www.isprs.org/.> (November 14, 2002).

SEE ALSO

Bomb Damage, Forensic Assessment
Cameras
Cuban Missile Crisis
Electromagnetic Spectrum
Electro-optical Intelligence
Geospatial Imagery
LIDAR (Light Detection and Ranging)
Photographic Resolution
Photography, High-Altitude
RADAR, Synthetic Aperture
U-2 Spy Plane
Unmanned Aerial Vehicles (UAVs)

Remote Sensing

Remote sensing is broadly defined as the act of obtaining images or data from a distance, typically using a manned spacecraft, a satellite, or a high-altitude spy aircraft. The term was invented in the 1950s to distinguish early satellite images from aerial photographs traditionally obtained from fixed wing aircraft. As such, remotely sensed images can be considered to be one kind of geospatial imagery . Although the application of unclassified remote sensing images to civil and criminal investigations has been limited, they have proven to be useful for documenting international atrocities in areas that are otherwise inaccessible to outside observers.

Sufficiently detailed satellite imagery has been used to document international crimes such as possible genocide in the Darfur region of Sudan and the existence of concealed mass graves in Iraq. In Iraq, potential gravesites were identified with the help of satellite image and aerial photograph interpretation and then investigated in more detail using ground-penetrating radar and other methods. A total of 270 mass graves were reported, of which 53 had been confirmed by early 2004, with some 400,000 bodies discovered. Features such as mass graves are generally not directly visible. Instead, analysis reveals features such as otherwise inexplicable areas of freshly moved earth or signs of heavy construction equipment used to excavate the graves. Comparison of publicly available Landsat satellite images obtained in 2003 and 2004 was also used to document the burning of 44 % of the villages in the Darfur region of Sudan during a period of civil strife, which some observers believe amounted to genocide. Burning was inferred in areas where the albedo, or amount of radiation reflected by the ground surface, had changed significantly during the times at which the two images were obtained. This was accomplished by using a computer algorithm to calculate albedo from the satellite data, then subtracting one albedo map from the other to calculate the change. This kind of mathematical operation on entire maps or digital images, as opposed to single numbers, is known as map algebra.

Modern remote sensing satellites provide panchromatic grayscale images (popularly known as black and white) and multispectral images in which channels representing discrete bands of the electromagnetic spectrum are combined. The most common multispectral images consist of some combination of red, green, blue, and near infrared bands. Hyperspectral sensors can produce images composed of dozens or hundreds of bands. Using information about the spectral reflectance characteristics of different kinds of soils , rocks, and plants, image analysts can fine tune the ratios of bands in multispectral and hyperspectral images to identify specific targets.

Image resolution has historically limited the use of satellite images, particularly those that are unclassified and easily available, in criminal and civil forensic work. The Landsat 1 satellite launched by the United States in the early 1970s, which provided the first publicly available satellite images, had a maximum resolution of 80 m. Therefore, objects smaller in size than several hundreds of meters could not be analyzed because objects must be many times larger than the maximum resolution in order to be clearly shown. Landsat 7, launched in 1999, had maximum resolution of 15 m for its panchromatic band, 30 m for its multispectral bands, and 60 m for its thermal infrared band. Although imagery with maximum resolution of 10 m or more can be useful for regional investigations, it is generally not useful for detailed forensic investigations of activities that have occurred through time on individual parcels of land. A new generation of commercial satellites such as the Quickbird satellite launched in 2001, however, has 0.61 m panchromatic resolution and 2.44 m multispectral resolution. The commercial IKONOS satellite, which was launched in 1999, has a maximum resolution of 1 m for color imagery. Although no images have been released as of early 2005, many intelligence experts believe that the most recent KeyHole surveillance satellites operated by the United States have a resolution of about 2 cm (0.02 m).

The resolution of panchromatic images is higher than that of multispectral or hyperspectral images because panchromatic information requirements are lower. In a panchromatic digital sensor, each light-sensitive photosite responds to all colors of light. In a multispectral sensor, however, the same number of photosites must be divided among each of the spectral bands. A multispectral sensor with infrared, red, green, and blue bands but the same number of photosites as a panchromatic sensor would have a resolution only 1/4 as high as the panchromatic sensor. This explains, for example, the ratio of 4 between the panchromatic 0.61 m resolution and multispectral 2.44 m resolution of the Quickbird satellite. In some cases, multispectral images can be combined with brightness information from more detailed panchromatic images. The apparent effect is a sharper image, although the resolution of the multispectral layer is not actually changed.

see also Digital imaging; Geospatial imagery; Satellites, non-governmental high resolution.

Remote Sensing

At its simplest definition, remote sensing is obtaining information about an object by a device that is not in contact with the object. In ecology remote sensing usually involves sensors on satellite platforms or airplanes. Most devices have a series of sensors that record the intensity of electromagnetic radiation in particular segments of the spectrum for each point, or pixel, in an image. These sensors are designed to collect data in the visible wavelength as well as in other portions of the electromagnetic spectrum (such as the infrared region) that are needed to examine specific aspects of the physical world.

In addition to collecting data from a large part of the electromagnetic spectrum, remote sensing systems collect data over large areas. For instance, the U.S. Landsat satellites record continuous data over an area 71.4 square miles (185 square kilometers) wide. Since some satellites have been in orbit since the mid-1970s scientists can effectively "collect data" from this time period. Therefore, remote sensing offers scientists a wide spectral, spatial, and temporal data range.

For remote sensing to be of use to ecologists the spectral data must be related to some ground-based measurement such as land cover type or vegetation characteristics (biomass or net primary production, evapotranspiration rates, water stress, vegetation structure). Most work in ecology is done at the scale of a small plot, or piece of a field or forest. It can be difficult to extrapolate these small-scale measurements to larger, heterogeneous areas. Because sensors record continuous data over large areas, remote sensing can be used to "scale-up" plot-based measurements to examine landscape or even regional patterns. For example, ecologists have used remote sensing data to determine the rate at which rainforest in Brazil is being converted to agricultural land. In North America, scientists using satellite data have determined that one of the most endangered ecosystems , the tallgrass prairie, is being replaced by woody vegetation at an alarming rate.

Another set of questions that can be addressed with remote sensing data involves landscape heterogeneity. In these analyses, any of a number of spatial statistics can be applied to the original spectral data. Also, the original bands can be recombined to create indices. The most common of these is the Normalized Difference Vegetation Index, a ratio of red to near infrared bands, which has been useful in quantifying vegetation in numerous locations around the world.

Spectral data can be analyzed directly (total infrared reflected) or a classification can be performed on the data. With this method, the spectral data are analyzed and each pixel is assigned to a land cover type: forest, grassland, or urban. For instance, forests reflect less infrared than grasslands. These land cover data can then be incorporated into a Geographical Information System (GIS) for further analysis. A GIS is a computer-based system that can deal with virtually any type of information that can be referenced by geographical location.

Once the land cover types are identified and GIS coverage is generated, additional data such as soil type, elevation, and land use history can be entered into the GIS. Ecologists can then ask questions about landscape-level patterns such as the average patch size of a certain land cover type or its dispersion across the landscape. This information can then be related to some ecological process such as the movement or dispersal of animals.

see also Ecology; Ecosystem; Grassland; Landscape Ecology

Greg A. Hoch and John M. Briggs

Bibliography

Lillesand, Thomas M., and Ralph W. Kiefer. Remote Sensing and Image Interpretation, 4th ed. New York: John Wiley & Sons, 1999.

Schott, John R. Remote Sensing: The Image Chain Approach. Oxford: Oxford University Press, 1996.

Schowengerdt, Robert A. Remote Sensing: Models and Methods for Image Processing. San Diego, CA: Academic Press, 1997.

remote sensing is the use of earth-observing satellites to study the oceans and their weather. The sensors either passively detect radiations coming from the earth's surface, or atmosphere, or they actively use radars to produce pulses of energy and then detect the energy reflected back. By using combinations of data from detectors of both visible and invisible light—that is, infra-red detectors—surface parameters like sea-surface temperatures and the concentrations of chlorophyll in the water can be estimated. However, corrections have to be applied to allow for the water vapour content of the air and the amount of suspended sediment in the water. Active radars of different frequency are used to measure surface wind speeds or as precision altimeters, which measure variations in the height of the sea surface caused by eddies or the waves (for illus. see gulf stream). The frequency of the radar and the altitude of the satellite influence the size of the footprint, the area of the surface observed. Observations may be averages of patches of ocean ranging from 25 metres (82 ft) to many kilometres across. The higher-frequency, short-wavelength radiations can ‘see’ through cloud, and can be used to detect some surprising features. For example, radars, which only detect the finest of ripples on the surface, can map underwater shoals in coastal waters. This is because, as tidal currents flow over these underwater features, they change the fine ripples on the surface.

The orbits of satellites are determined according to the phenomena being observed. Those used for satellite navigation, like GPS, are geo-stationary, orbiting synchronously with the earth; others have tracks that are constantly repeated or follow tracks which shift, so the whole surface is observed every few days. Remote sensing has given those studying oceanography and marine meteorology the ability to observe the global oceans, but unfortunately it does not detect ocean conditions at depth.

M. V. Angel

remote sensing Any technique for obtaining information about an object without coming into direct contact with it. In this broad sense it includes all the techniques used in ground-based and space astronomy. In terrestrial studies it refers particularly to satellite‐borne instrumentation designed to observe features on or above the Earth's surface. Sophisticated remote-sensing techniques, such as synthetic-aperture radar, have been responsible for enormous improvements in our knowledge of the surface of Venus, for example. Spectroscopic methods such as infrared radiometry and colorimetry have been used to study the surface compositions of asteroids.

remote sensing Any method of obtaining and recording information from a distance. The most common sensor is the camera; cameras are used in aircraft, satellites, and space probes to collect information and transmit it back to Earth (often by radio). The resulting photographs provide a variety of information, including archeological evidence and weather data. The images are also used in map-making. Microwave sensors use radar signals that penetrate cloud. Infrared sensors measure temperature differences over an area. Computers process data from sensors.

remote sensing The technique whereby sensors located remotely from a computer are used to produce inputs for a digital system. These inputs are then transmitted either by wire or radio techniques to the computer. An example is the use of digital thermometers and humidity detectors in large buildings: the sensors transmit their readings to a central computer that optimizes energy use by regulating heat and air conditioning.

remote sensing The gathering of information without actual physical contact with what is being observed. This involves the use of radars, sonars, spectrosocopy, and the use of airborne and satellite photography. See BISTATIC RADAR; IMAGING; LASER RANGING; POLARIMETRY; RADAR ALTIMETRY; RADIOMETRY; and RADIO OCCULTATION.

remote sensing the scanning of the earth by satellite or high-flying aircraft in order to obtain information about it.