Radiometry

A radar antenna.

• Radar may be used for ranging and velocity measurements of hard targets (i.e. an aircraft) or distributed targets (such as a cloud of water vapor, or plasmas in the ionosphere). Synthetic aperture radar can produce precise Digital elevation models of terrain (See RADARSAT, Magellan).
• Laser and radar altimeters on satellites have provided a wide range of data. By measuring the bulges of water caused by gravity, they map features on the seafloor to a resolution of a mile or so. By measuring the height and wave-length of ocean waves, the altimeters measure wind speeds and direction, and surface ocean currents and directions.
• Lidar may be used to measure the concentration of various chemical species in the atmosphere as well as ranging.
• Radiometers and photometers may be used to detect the emission spectra of various chemical species, thus providing information on chemical concentrations in the atmosphere.
• Stereographic pairs of aerial photographs have often been used to make Topographic maps. Satellite imagery has also been used.
• Thematic mappers take images in multiple wavelengths of electro-magnetic radiation (multi-spectral) and are usually found on earth observation satellites, including (for example) the Landsat program or the IKONOS satellite. Maps of land cover and land use from thematic mapping can be used to prospect for minerals, measure land usage, and examine the health of plants, including entire farming regions or forests.

Geodesy

• Satellite measurements of minute perturbations in the Earth's gravitational field (geodesy) may be used to determine changes in the mass distrubution of the Earth, which in turn may be used for geological or hydrological studies.

Acoustics

Cabin display of a fish finder sonar

• Sonar may be utilized for ranging and measurements of underwater objects and terrain.
• Seismograms taken at different locations can locate and measure Earthquakes (after the fact) by comparing the relative intensity and precise timing.

In order to coordinate a series of observations, most sensing systems need to know where they are, what time it is, and the rotation and orinetation of the instrument. High-end instruments now often use positional information from satellite navigation systems. The rotation and orientation is often provided within a degree or two with electronic compasses. Compasses can measure not just azimuth (i.e. degrees to magnetic north), but also altitude (degrees above the horizon), since the magnetic field curves into the Earth at different angles at different latitudes. More exact orientations require gyroscopic pointing information, periodically realigned in some fashion, perhaps from a star or the limb of the Earth.

The resolution determines how many pixels are available in measurement, but more importantly, higher resolutions are more informative, giving more data about more points. However, more resolution occasionally yields less data. For example, in thematic mapping to study plant health, imaging individual leaves of plants is actually counterproductive. Also, large amounts of high resolution data can clog a storage or transmission system with useless data, when a few low resolution images might be a better use of the system.

Data processing

Generally speaking, remote sensing works on the principle of the inverse problem. While the object or phenomenon of interest (the state) may not be directly measured, there exists some other variable that can be measured (the observation), which may be related to the object of interest via some (usually mathematical) model. The common analogy given to describe this is trying to determine the type of animal from its footprints. For example, while it is impossible to directly measure temperatures in the upper atmosphere, it is possible to measure the spectral emissions from a known chemical species (such as carbon dioxide) in that region. The frequency of the emission may then be related to the temperature in that region via various thermodynamic relations.

The quality of remote sensing data consists of its spatial, spectral, radiometric and temporal resolutions. Spatial resolution refers to the size of a pixel that is recorded in a raster image - typically pixels may correspond to square areas ranging in side length from 1 to 1000 metres. Spectral resolution refers to the number of different frequency bands recorded - usually, this is equivalent to the number of sensors carried by the satellite or plane. Landsat images have seven bands, including several in the infra-red spectrum. The MODIS satellites are the highest resolving at 31 bands. Radiometric resolution refers to the number of different intensities of radiation the sensor is able to distinguish. Typically, this ranges from 8 to 14 bits, corresponding to 256 to 16,384 intensities or "shades" of colour, in each band. The temporal resolution is simply the frequency of flyovers by the satellite or plane, and is only relevant in time-series studies or those requiring an averaged or mosaic image. This may be necessary to avoid cloud cover. Finally, some people also refer to the "economic resolution", that is, how much data you get or are able to process per unit money.

In order to generate maps, most remote sensing systems expect to convert a photograph or other data item to a distance on the ground. This almost always depends on the precision of the instrument. For example, distortion in an aerial photographic lens or the platen against which the film is pressed can cause severe errors when photographs are used to measure ground distances. The step in which this problem is resolved is called georeferencing, and involves matching up points in the image (typically 30 or more points per image) with points in a precise map, or in a previously georeferenced image, and finally "warping" the image to reduce any distortions. As of the early 1990s, most satellite images are sold fully georeferenced.

In addition, images may need to be radiometrically and atmospherically corrected. Radiometric correction gives a scale to the pixel values, e.g. the scale of 0 to 255 will be converted to actual radiance values. Atmospheric correction eliminates atmospheric haze by rescaling each frequency band so that its minimum value (usually realised in water bodies) corresponds to a pixel value of 0.

Interpretation is the critical process of making sense of the data. Traditionally, this was a human being, perhaps with a few measurement tools and a light table, but the analyses are becoming increasingly sophisticated and automated.

Old data from remote sensing is often valuable because it may provide the only long-term data for a large extent of geography. At the same time, the data is often complex to interpret, and bulky to store. Modern systems tend to store the data digitally, often with lossless compression. The difficulty with this approach is that the data is fragile, the format may be archaic, and the data may be easy to falsify. One of the best systems for archiving data series is as computer-generated machine-readeable ultrafiche, usually in typefonts such as OCR-B, or as digitized half-tone images. Ultrafiches survive well in standard libraries, with lifetimes of several centuries. They can be created, copied, filed and retrieved by automated systems. They are about as compact as archival magnetic media, and yet can be read by human beings with minimal, standardized equipment.

History

The U-2 reconnaissance aircraft.

The 2001 Mars Odyssey Spacecraft used spectrometers and imagers to hunt for evidence of past or present water and volcanic activity on Mars.

Beyond the primitive methods of remote sensing our earliest ancestors used (ex.: standing on a high cliff or tree to view the landscape), the modern discipline arose with the development of flight. The balloonist G. Tournachon (alias Nadar), who made photographs of Paris from his balloon in 1858, is considered to be the first aerial photographer. Messenger pigeons, kites, rockets and unmanned balloons were also used for early images. These first, individual images were not particularly useful for map making or for scientific purposes.

Systematic aerial photography was developed for military purposes beginning in World War I and reaching a climax during the Cold War with the development of reconnaissance aircraft such as the U-2.

The development of artificial satellites in the latter half of the 20th century allowed remote sensing to progress to a global scale. Instrumentation aboard various Earth observing and weather satellites such as Landsat, the Nimbus and more recent missions such as RADARSAT and UARS provided global measurements of various data for civil, scientific, and military purposes. Space probes to other planets have also provided the opportunity to conduct remote sensing studies in extra-terrestrial environments, synthetic aperture radar aboard the Magellan spacecraft provided detailed topographic maps of Venus, while instruments aboard SOHO allowed studies to be performed on the Sun and the solar wind, just to name a few examples.

Further strides were made in the 1960s and 1970s with the development of image processing of satellite imagery, beginning in the United States. Several research groups in Silicon Valley including NASA Ames Research Center, GTE and ESL Inc. developed Fourier transform techniques leading to the first notable image enhancement of aerial photographs.