Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object and thus in contrast to on-site observation, especially the Earth. Remote sensing is used in numerous fields, including geography, land surveying and most Earth Science disciplines (for example, hydrology, ecology, meteorology, oceanography, glaciology, geology); it also has military, intelligence, commercial, economic, planning, and humanitarian applications.
Ecology is a branch of biology that studies the interactions among organisms and their biophysical environment, which includes both biotic and abiotic components. Topics of interest include the biodiversity, distribution, biomass, and populations of organisms, as well as cooperation and competition within and between species. Ecosystems are dynamically interacting systems of organisms, the communities they make up, and the non-living components of their environment. Ecosystem processes, such as primary production, pedogenesis, nutrient cycling, and niche construction, regulate the flux of energy and matter through an environment. These processes are sustained by organisms with specific life history traits.
In current usage, the term "remote sensing" generally refers to the use of satellite- or aircraft-based sensor technologies to detect and classify objects on Earth, including on the surface and in the atmosphere and oceans, based on propagated signals (e.g. electromagnetic radiation). It may be split into "active" remote sensing (such as when a signal is emitted by a satellite or aircraft and its reflection by the object is detected by the sensor) and "passive" remote sensing (such as when the reflection of sunlight is detected by the sensor).
An atmosphere is a layer or a set of layers of gases surrounding a planet or other material body, that is held in place by the gravity of that body. An atmosphere is more likely to be retained if the gravity it is subject to is high and the temperature of the atmosphere is low.
Wave propagation is any of the ways in which waves travel.
In physics, electromagnetic radiation refers to the waves of the electromagnetic field, propagating (radiating) through space, carrying electromagnetic radiant energy. It includes radio waves, microwaves, infrared, (visible) light, ultraviolet, X-rays, and gamma rays.
Passive sensors gather radiation that is emitted or reflected by the object or surrounding areas. Reflected sunlight is the most common source of radiation measured by passive sensors. Examples of passive remote sensors include film photography, infrared, charge-coupled devices, and radiometers. Active collection, on the other hand, emits energy in order to scan objects and areas whereupon a sensor then detects and measures the radiation that is reflected or backscattered from the target. RADAR and LiDAR are examples of active remote sensing where the time delay between emission and return is measured, establishing the location, speed and direction of an object.
Sunlight is a portion of the electromagnetic radiation given off by the Sun, in particular infrared, visible, and ultraviolet light. On Earth, sunlight is filtered through Earth's atmosphere, and is obvious as daylight when the Sun is above the horizon. When the direct solar radiation is not blocked by clouds, it is experienced as sunshine, a combination of bright light and radiant heat. When it is blocked by clouds or reflects off other objects, it is experienced as diffused light. The World Meteorological Organization uses the term "sunshine duration" to mean the cumulative time during which an area receives direct irradiance from the Sun of at least 120 watts per square meter. Other sources indicate an "Average over the entire earth" of "164 Watts per square meter over a 24 hour day".
Photography is the art, application and practice of creating durable images by recording light or other electromagnetic radiation, either electronically by means of an image sensor, or chemically by means of a light-sensitive material such as photographic film. It is employed in many fields of science, manufacturing, and business, as well as its more direct uses for art, film and video production, recreational purposes, hobby, and mass communication.
Infrared radiation (IR), sometimes called infrared light, is electromagnetic radiation (EMR) with longer wavelengths than those of visible light, and is therefore generally invisible to the human eye, although IR at wavelengths up to 1050 nanometers (nm)s from specially pulsed lasers can be seen by humans under certain conditions. IR wavelengths extend from the nominal red edge of the visible spectrum at 700 nanometers, to 1 millimeter (300 GHz). Most of the thermal radiation emitted by objects near room temperature is infrared. As with all EMR, IR carries radiant energy and behaves both like a wave and like its quantum particle, the photon.
Remote sensing makes it possible to collect data of dangerous or inaccessible areas. Remote sensing applications include monitoring deforestation in areas such as the Amazon Basin, glacial features in Arctic and Antarctic regions, and depth sounding of coastal and ocean depths. Military collection during the Cold War made use of stand-off collection of data about dangerous border areas. Remote sensing also replaces costly and slow data collection on the ground, ensuring in the process that areas or objects are not disturbed.
Deforestation, clearance, clearcutting or clearing is the removal of a forest or stand of trees from land which is then converted to a non-forest use. Deforestation can involve conversion of forest land to farms, ranches, or urban use. The most concentrated deforestation occurs in tropical rainforests. About 31% of Earth's land surface is covered by forests.
A glacier is a persistent body of dense ice that is constantly moving under its own weight; it forms where the accumulation of snow exceeds its ablation over many years, often centuries. Glaciers slowly deform and flow due to stresses induced by their weight, creating crevasses, seracs, and other distinguishing features. They also abrade rock and debris from their substrate to create landforms such as cirques and moraines. Glaciers form only on land and are distinct from the much thinner sea ice and lake ice that form on the surface of bodies of water.
Depth sounding refers to the act of measuring depth. It is often referred to simply as sounding. Data taken from soundings are used in bathymetry to make maps of the floor of a body of water, and were traditionally shown on nautical charts in fathoms and feet. The National Oceanic and Atmospheric Administration (NOAA), the agency responsible for bathymetric data in the United States, still uses fathoms and feet on nautical charts. In other countries, the International System of Units (metres) has become the standard for measuring depth.
Orbital platforms collect and transmit data from different parts of the electromagnetic spectrum, which in conjunction with larger scale aerial or ground-based sensing and analysis, provides researchers with enough information to monitor trends such as El Niño and other natural long and short term phenomena. Other uses include different areas of the earth sciences such as natural resource management, agricultural fields such as land usage and conservation,and national security and overhead, ground-based and stand-off collection on border areas.
The electromagnetic spectrum is the range of frequencies of electromagnetic radiation and their respective wavelengths and photon energies.
El Niño is the warm phase of the El Niño–Southern Oscillation (ENSO) and is associated with a band of warm ocean water that develops in the central and east-central equatorial Pacific, including the area off the Pacific coast of South America. The ENSO is the cycle of warm and cold sea surface temperature (SST) of the tropical central and eastern Pacific Ocean. El Niño is accompanied by high air pressure in the western Pacific and low air pressure in the eastern Pacific. El Niño phases are known to occur close to four years, however, records demonstrate that the cycles have lasted between two and seven years. During the development of El Niño, rainfall develops between September–November. The cool phase of ENSO is La Niña, with SSTs in the eastern Pacific below average, and air pressure high in the eastern Pacific and low in the western Pacific. The ENSO cycle, including both El Niño and La Niña, causes global changes in temperature and rainfall.
Earth science or geoscience includes all fields of natural science related to the planet Earth. This is a branch of science dealing with the physical constitution of the Earth and its atmosphere. Earth science is the study of our planet's physical characteristics, from earthquakes to raindrops, and floods to fossils. Earth science can be considered to be a branch of planetary science, but with a much older history. Earth science encompasses four main branches of study, the lithosphere, the hydrosphere, the atmosphere, and the biosphere, each of which is further broken down into more specialized fields.
The basis for multispectral collection and analysis is that of examined areas or objects that reflect or emit radiation that stand out from surrounding areas. For a summary of major remote sensing satellite systems see the overview table.
A variety of remote sensing systems exist, for which the specification is distributed among a variety of websites from data providers, satellite operators and manufacturers. In order to choose a data product for a given project, a remote sensing data user must be aware of the different products and their applications. The table below gives users an overview of major remote sensing systems and datasets and summarizes their applications and systems.
To coordinate a series of large-scale observations, most sensing systems depend on the following: platform location and the orientation of the sensor. 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-aided orientation, periodically realigned by different methods including navigation from stars or known benchmarks.
The quality of remote sensing data consists of its spatial, spectral, radiometric and temporal resolutions.
In order to create sensor-based maps, most remote sensing systems expect to extrapolate sensor data in relation to a reference point including distances between known points on the ground. This depends on the type of sensor used. For example, in conventional photographs, distances are accurate in the center of the image, with the distortion of measurements increasing the farther you get from the center. Another factor is that of 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 computer-aided matching of points in the image (typically 30 or more points per image) which is extrapolated with the use of an established benchmark, "warping" the image to produce accurate spatial data. As of the early 1990s, most satellite images are sold fully georeferenced.
In addition, images may need to be radiometrically and atmospherically corrected.
Interpretation is the critical process of making sense of the data. The first application was that of aerial photographic collection which used the following process; spatial measurement through the use of a light table in both conventional single or stereographic coverage, added skills such as the use of photogrammetry, the use of photomosaics, repeat coverage, Making use of objects’ known dimensions in order to detect modifications. Image Analysis is the recently developed automated computer-aided application which is in increasing use.
Object-Based Image Analysis (OBIA) is a sub-discipline of GIScience devoted to partitioning remote sensing (RS) imagery into meaningful image-objects, and assessing their characteristics through spatial, spectral and temporal scale.
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-readable 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.
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 detected and measured (the observation) which may be related to the object of interest through a calculation. 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 emissions may then be related via thermodynamics to the temperature in that region.
To facilitate the discussion of data processing in practice, several processing "levels" were first defined in 1986 by NASA as part of its Earth Observing Systemand steadily adopted since then, both internally at NASA (e. g., ) and elsewhere (e. g., ); these definitions are:
|0||Reconstructed, unprocessed instrument and payload data at full resolution, with any and all communications artifacts (e. g., synchronization frames, communications headers, duplicate data) removed.|
|1a||Reconstructed, unprocessed instrument data at full resolution, time-referenced, and annotated with ancillary information, including radiometric and geometric calibration coefficients and georeferencing parameters (e. g., platform ephemeris) computed and appended but not applied to the Level 0 data (or if applied, in a manner that level 0 is fully recoverable from level 1a data).|
|1b||Level 1a data that have been processed to sensor units (e. g., radar backscatter cross section, brightness temperature, etc.); not all instruments have Level 1b data; level 0 data is not recoverable from level 1b data.|
|2||Derived geophysical variables (e. g., ocean wave height, soil moisture, ice concentration) at the same resolution and location as Level 1 source data.|
|3||Variables mapped on uniform spacetime grid scales, usually with some completeness and consistency (e. g., missing points interpolated, complete regions mosaicked together from multiple orbits, etc.).|
|4||Model output or results from analyses of lower level data (i. e., variables that were not measured by the instruments but instead are derived from these measurements).|
A Level 1 data record is the most fundamental (i. e., highest reversible level) data record that has significant scientific utility, and is the foundation upon which all subsequent data sets are produced. Level 2 is the first level that is directly usable for most scientific applications; its value is much greater than the lower levels. Level 2 data sets tend to be less voluminous than Level 1 data because they have been reduced temporally, spatially, or spectrally. Level 3 data sets are generally smaller than lower level data sets and thus can be dealt with without incurring a great deal of data handling overhead. These data tend to be generally more useful for many applications. The regular spatial and temporal organization of Level 3 datasets makes it feasible to readily combine data from different sources.
While these processing levels are particularly suitable for typical satellite data processing pipelines, other data level vocabularies have been defined and may be appropriate for more heterogeneous workflows.
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The modern discipline of remote sensing arose with the development of flight. The balloonist G. Tournachon (alias Nadar) made photographs of Paris from his balloon in 1858.Messenger pigeons, kites, rockets and unmanned balloons were also used for early images. With the exception of balloons, these first, individual images were not particularly useful for map making or for scientific purposes.
Systematic aerial photography was developed for military surveillance and reconnaissance purposes beginning in World War Iand reaching a climax during the Cold War with the use of modified combat aircraft such as the P-51, P-38, RB-66 and the F-4C, or specifically designed collection platforms such as the U2/TR-1, SR-71, A-5 and the OV-1 series both in overhead and stand-off collection. A more recent development is that of increasingly smaller sensor pods such as those used by law enforcement and the military, in both manned and unmanned platforms. The advantage of this approach is that this requires minimal modification to a given airframe. Later imaging technologies would include infrared, conventional, Doppler and synthetic aperture radar.
The development of artificial satellites in the latter half of the 20th century allowed remote sensing to progress to a global scale as of the end of the Cold War.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, research, and military purposes. Space probes to other planets have also provided the opportunity to conduct remote sensing studies in extraterrestrial 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.
Recent developments include, beginning in the 1960s and 1970s with the development of image processing of satellite imagery. Several research groups in Silicon Valley including NASA Ames Research Center, GTE, and ESL Inc. developed Fourier transform techniques leading to the first notable enhancement of imagery data. In 1999 the first commercial satellite (IKONOS) collecting very high resolution imagery was launched.
Remote Sensing has a growing relevance in the modern information society. It represents a key technology as part of the aerospace industry and bears increasing economic relevance – new sensors e.g. TerraSAR-X and RapidEye are developed constantly and the demand for skilled labour is increasing steadily. Furthermore, remote sensing exceedingly influences everyday life, ranging from weather forecasts to reports on climate change or natural disasters. As an example, 80% of the German students use the services of Google Earth; in 2006 alone the software was downloaded 100 million times. But studies have shown that only a fraction of them know more about the data they are working with.There exists a huge knowledge gap between the application and the understanding of satellite images. Remote sensing only plays a tangential role in schools, regardless of the political claims to strengthen the support for teaching on the subject. A lot of the computer software explicitly developed for school lessons has not yet been implemented due to its complexity. Thereby, the subject is either not at all integrated into the curriculum or does not pass the step of an interpretation of analogue images. In fact, the subject of remote sensing requires a consolidation of physics and mathematics as well as competences in the fields of media and methods apart from the mere visual interpretation of satellite images.
Many teachers have great interest in the subject "remote sensing", being motivated to integrate this topic into teaching, provided that the curriculum is considered. In many cases, this encouragement fails because of confusing information.In order to integrate remote sensing in a sustainable manner organizations like the EGU or Digital Earth encourage the development of learning modules and learning portals. Examples include: FIS – Remote Sensing in School Lessons, Geospektiv, Ychange, or Spatial Discovery, to promote media and method qualifications as well as independent learning.
Remote sensing data are processed and analyzed with computer software, known as a remote sensing application. A large number of proprietary and open source applications exist to process remote sensing data. Remote sensing software packages include:
Open source remote sensing software includes:
According to an NOAA Sponsored Research by Global Marketing Insights, Inc. the most used applications among Asian academic groups involved in remote sensing are as follows: ERDAS 36% (ERDAS IMAGINE 25% & ERMapper 11%); ESRI 30%; ITT Visual Information Solutions ENVI 17%; MapInfo 17%.
Among Western Academic respondents as follows: ESRI 39%, ERDAS IMAGINE 27%, MapInfo 9%, and AutoDesk 7%.
In education, those that want to go beyond simply looking at satellite images print-outs either use general remote sensing software (e.g. QGIS), Google Earth, StoryMaps or a software/ web-app developed specifically for education (e.g. desktop: LeoWorks, online: BLIF).
First satellite UV/VIS observations simply showed pictures of the Earth's surface and atmosphere. Such satellite images are still used, for instance as input for numerical weather forecast. The first spectroscopic UV/VIS observations started in 1970 on board of the US research satellite Nimbus 4. These measurements (backscatter ultraviolet, BUV, later also called Solar BUV, SBUV) operated in nadir geometry, i.e., they measured the solar light reflected from the ground or scattered from the atmosphere. Like for the Dobson instruments also the BUV/SBUV instruments measure the intensity in different narrow spectral intervals. The intention of these BUV/SBUV observations was to determine information on the atmospheric O3 profile, since the penetration depth into the atmosphere strongly depends on wavelength. For example, the light at the shortest wavelengths has only 'seen' the highest parts of the O3 layer whereas the longest wavelengths have seen the total column. While in principle the BUV/SBUV measurements worked well, they suffered from instrumental instabilities.
The big breakthrough[ according to whom? ] in UV/VIS satellite remote sensing of the atmosphere took place in 1979 with the launch the Total Ozone Mapping Spectrometer (TOMS) on Nimbus 7. TOMS is similar to the BUV/SBUV instrument but measures light at longer wavelengths. Thus it is only sensitive to the total O3 column (instead of the O3 profile). However, compared to the BUV/SBUV instruments the TOMS instruments were much more stable. The TOMS instrument on board of Nimbus 7 yielded the so far longest global data set on O3 (1979–1992). This period in particular includes the discovery of the ozone hole. Several further TOMS instruments have been launched on other satellites. Like the Dobson instruments on the ground they yield very accurate O3 total column densities using a relatively simple method. Besides events of very strong atmospheric SO2 absorption and aerosols they are, however, only sensitive to O3.
Since April 1995 the first DOAS instrument is operating from space. The Global Ozone Monitoring Experiment (GOME) was launched on the European research satellite ERS-2. Like SBUV and TOMS also GOME is a nadir viewing instrument; unlike its predecessor instruments it covers a large spectral range (240 – 790 nm) at a total of 4096 wavelengths arranged in four 'channels' with a spectral resolution between 0.2 and 0.4 nm. Its normal ground pixel size in 320 × 40 km2. Global coverage is achieved after three days. For O3 profile measurements the intensities at short wavelengths are observed (BUV/SBUV instruments). For the determination of the total atmospheric O3 column the intensities at larger wavelengths are used (TOMS instruments). In contrast to the limited spectral information of BUV/SBUV and TOMS instruments, GOME spectra yield a surplus of spectral information. By applying the DOAS method to these measurements it is thus possible to retrieve a large variety of atmospheric trace gases, the majority of which are very weak absorbers (O3, NO2, BrO, OClO, HCHO, H2O, O2, O4, SO2). In addition other quantities like aerosol absorptions, the ground albedo or indices characterising the solar cycle can be analysed. Because of the high sensitivity of GOME it is in particular possible to measure various tropospheric trace gases (NO2, BrO, HCHO, H2O, SO2). A further important advantage is that the GOME spectra can be analysed with respect to a spectrum of direct sun light, which contains no atmospheric absorptions. Therefore, in contrast to ground based DOAS measurements the DOAS analysis of GOME spectra yields total atmospheric column densities rather than the difference between two atmospheric spectra.
In March 2002 a second DOAS satellite instrument, the SCanning Imaging Absorption SpectroMeter for Atmospheric ChartographY (SCIAMACHY) was launched on board of the European research satellite Envisat. In addition to GOME it measures over a wider wavelength range (240 nm – 2380) including also the absorption of several greenhouse gases (CO2, CH4, N2O) and CO in the IR. It also operated in additional viewing modes (nadir, limb, occultation), which allows to derive stratospheric trace gas profiles. Another advantage is that the ground pixel size for the nadir viewing mode was significantly reduced to 30 x 60 km2 (in a special mode even to 15 x 30 km2). Especially for the observation of tropospheric trace gases this is very important because of the strong spatial gradients occurring for such species. The first tropospheric results of SCIAMACHY showed that it was now possible to identify pollution plumes of individual cities or other big sources.
Lidar is a surveying method that measures distance to a target by illuminating the target with laser light and measuring the reflected light with a sensor. Differences in laser return times and wavelengths can then be used to make digital 3-D representations of the target. The name lidar, now used as an acronym of light detection and ranging, was originally a portmanteau of light and radar. Lidar sometimes is called 3D laser scanning, a special combination of a 3D scanning and laser scanning. It has terrestrial, airborne, and mobile applications.
Envisat is a large inactive Earth-observing satellite which is still in orbit. Operated by the European Space Agency (ESA), it was the world's largest civilian Earth observation satellite.
A microwave radiometer (MWR) is a radiometer that measures energy emitted at millimetre-to-centimetre wavelengths known as microwaves. Microwave radiometers are very sensitive receivers designed to measure thermal electromagnetic radiation emitted by atmospheric gases. They are usually equipped with multiple receiving channels in order to derive the characteristic emission spectrum of the atmosphere or extraterrestrial objects. Microwave radiometers are utilized in a variety of environmental and engineering applications, including weather forecasting, climate monitoring, radio astronomy and radio propagation studies.
The multi-angle imaging spectroradiometer (MISR) is a scientific instrument on the Terra satellite launched by NASA on 18 December 1999. This device is designed to measure the intensity of solar radiation reflected by the Earth system in various directions and spectral bands; it became operational in February 2000. Data generated by this sensor have been proven useful in a variety of applications including atmospheric sciences, climatology and monitoring terrestrial processes.
The Moderate Resolution Imaging Spectroradiometer (MODIS) is a payload imaging sensor built by Santa Barbara Remote Sensing that was launched into Earth orbit by NASA in 1999 on board the Terra satellite, and in 2002 on board the Aqua satellite. The instruments capture data in 36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm and at varying spatial resolutions. Together the instruments image the entire Earth every 1 to 2 days. They are designed to provide measurements in large-scale global dynamics including changes in Earth's cloud cover, radiation budget and processes occurring in the oceans, on land, and in the lower atmosphere. MODIS utilizes four on-board calibrators in addition to the space view in order to provide in-flight calibration: solar diffuser (SD), solar diffuser stability monitor (SDSM), spectral radiometric calibration assembly (SRCA), and a v-groove black body. MODIS has used the marine optical buoy for vicarious calibration. MODIS is succeeded by the VIIRS instrument on board the Suomi NPP satellite launched in 2011 and future Joint Polar Satellite System (JPSS) satellites.
Measurement and signature intelligence (MASINT) is a technical branch of intelligence gathering, which serves to detect, track, identify or describe the distinctive characteristics (signatures) of fixed or dynamic target sources. This often includes radar intelligence, acoustic intelligence, nuclear intelligence, and chemical and biological intelligence. MASINT is defined as scientific and technical intelligence derived from the analysis of data obtained from sensing instruments for the purpose of identifying any distinctive features associated with the source, emitter or sender, to facilitate the latter’s measurement and identification.
Atmospheric physics is the application of physics to the study of the atmosphere. Atmospheric physicists attempt to model Earth's atmosphere and the atmospheres of the other planets using fluid flow equations, chemical models, radiation budget, and energy transfer processes in the atmosphere. In order to model weather systems, atmospheric physicists employ elements of scattering theory, wave propagation models, cloud physics, statistical mechanics and spatial statistics which are highly mathematical and related to physics. It has close links to meteorology and climatology and also covers the design and construction of instruments for studying the atmosphere and the interpretation of the data they provide, including remote sensing instruments. At the dawn of the space age and the introduction of sounding rockets, aeronomy became a subdiscipline concerning the upper layers of the atmosphere, where dissociation and ionization are important.
Satellite imagery are images of Earth or other planets collected by imaging satellites operated by governments and businesses around the world. Satellite imaging companies sell images by licensing them to governments and businesses such as Apple Maps and Google Maps.
A multispectral image is one that captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or by the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, i.e. infrared and ultra-violet. Spectral imaging can allow extraction of additional information the human eye fails to capture with its receptors for red, green and blue. It was originally developed for space-based imaging, and has also found use in document and painting analysis.
Spectral imaging is imaging that uses multiple bands across the electromagnetic spectrum. While an ordinary camera captures light across three wavelength bands in the visible spectrum, red, green, and blue (RGB), spectral imaging encompasses a wide variety of techniques that go beyond RGB. Spectral imaging may use the infrared, the visible spectrum, the ultraviolet, x-rays, or some combination of the above. It may include the acquisition of image data in visible and non-visible bands simultaneously, illumination from outside the visible range, or the use of optical filters to capture a specific spectral range. It is also possible to capture hundreds of wavelength bands for each pixel in an image.
In imaging spectroscopy each pixel of an image acquires many bands of light intensity data from the spectrum, instead of just the three bands of the RGB color model. More precisely, it is the simultaneous acquisition of spatially coregistered images in many spectrally contiguous bands.
The normalized difference vegetation index (NDVI) is a simple graphical indicator that can be used to analyze remote sensing measurements, typically, but not necessarily, from a space platform, and assess whether the target being observed contains live green vegetation or not.
Hyperspectral imaging, like other spectral imaging, collects and processes information from across the electromagnetic spectrum. The goal of hyperspectral imaging is to obtain the spectrum for each pixel in the image of a scene, with the purpose of finding objects, identifying materials, or detecting processes. There are two general branches of spectral imagers. There are push broom scanners and the related whisk broom scanners, which read images over time, and snapshot hyperspectral imaging, which uses a staring array to generate an image in an instant.
Electro-optical MASINT is a subdiscipline of Measurement and Signature Intelligence, (MASINT) and refers to intelligence gathering activities which bring together disparate elements that do not fit within the definitions of Signals Intelligence (SIGINT), Imagery Intelligence (IMINT), or Human Intelligence (HUMINT).
The Solar Backscatter Ultraviolet Radiometer, or SBUV/2, is a series of operational remote sensors on NOAA weather satellites in Sun-synchronous orbits which have been providing global measurements of stratospheric total ozone, as well as ozone profiles, since March 1985. The SBUV/2 instruments were developed from the SBUV experiment flown on the Nimbus-7 spacecraft which improved on the design of the original BUV instrument on Nimbus-4. These are nadir viewing radiometric instruments operating at mid to near UV wavelengths. SBUV/2 data sets overlap with data from SBUV and TOMS instruments on the Nimbus-7 spacecraft. These extensive data sets measure the density and vertical distribution of ozone in the Earth's atmosphere from six to 30 miles.
Earth Observing-1 (EO-1) is a decommissioned NASA Earth observation satellite created to develop and validate a number of instrument and spacecraft bus breakthrough technologies. It was intended to enable the development of future Earth imaging observatories that will have a significant increase in performance while also having reduced cost and mass. The spacecraft was part of the New Millennium Program. It was the first satellite to map active lava flows from space; the first to measure a facility's methane leak from space; and the first to track re-growth in a partially logged Amazon forest from space. EO-1 captured scenes such as the ash after the World Trade Center attacks, the flooding in New Orleans after Hurricane Katrina, volcanic eruptions and a large methane leak in southern California.
Multispectral remote sensing is the collection and analysis of reflected, emitted, or back-scattered energy from an object or an area of interest in multiple bands of regions of the electromagnetic spectrum. Subcategories of multispectral remote sensing include hyperspectral, in which hundreds of bands are collected and analyzed, and ultraspectral remote sensing where many hundreds of bands are used. The main purpose of multispectral imaging is the potential to classify the image using multispectral classification. This is a much faster method of image analysis than is possible by human interpretation.
PRISMA is an Italian Space Agency pre-operational and technology demonstrator mission focused on the development and delivery of hyperspectral products and the qualification of the hyperspectral payload in space.
Sentinel-4 is a satellite mission making up a part of the European Copernicus Programme, which is also known as the European Global Monitoring for Environment and Security (GMES) programme. Sentinel-4 will utilize 2 payload instruments integrated on board a Meteosat Third Generation Sounder (MTG-S) satellite to observe primarily the tropospheric composition of the Earth's atmosphere. The data will be gathered and made available to the Copernicus program with the aim of contributing to air quality applications such as with the Copernicus Atmosphere Services as well as the air quality monitoring over the regions of Europe and Northern Africa. As with other aspects of the Copernicus programme, the Sentinel-4 initiative is funded mostly through the EU and the technical design and development has been put under responsibility of the European Space Agency (ESA).
Remote sensing in geology is remote sensing used in the geological sciences as a data acquisition method complementary to field observation, because it allows mapping of geological characteristics of regions without physical contact with the areas being explored. About one-fourth of the Earth's total surface area is exposed land where information is ready to be extracted from detailed earth observation via remote sensing. Remote sensing is conducted via detection of electromagnetic radiation by sensors. The radiation can be naturally sourced, or produced by machines and reflected off of the Earth surface. The electromagnetic radiation acts as an information carrier for two main variables. First, the intensities of reflectance at different wavelengths are detected, and plotted on a spectral reflectance curve. This spectral fingerprint is governed by the physio-chemical properties of the surface of the target object and therefore helps mineral identification and hence geological mapping, for example by hyperspectral imaging. Second, the two-way travel time of radiation from and back to the sensor can calculate the distance in active remote sensing systems, for example, Interferometric synthetic-aperture radar. This helps geomorphological studies of ground motion, and thus can illuminate deformations associated with landslides, earthquakes, etc.