[Excerpted from my book Remote Sensing and GIS]
Remote sensing is a complex technique and may vary based on the application and technological development. Considering technological development, for example, in the earlier days remote sensing was performed from balloons, but nowadays satellites are being used. Earlier, photographic cameras remained the only option, but nowadays digital cameras/sensors are dominating. Considering applications, for example, mapping purposes can be fulfilled by optical images, but information about temperature needs thermal image.
Remote sensing may be classified from many perspectives, for example, based on platform, source of energy, number of bands, and so on. The following sections explain remote sensing from the perspective of different classification schemes.
Classification Based on Platform
In order for a remote sensor to collect and record energy reflected or emitted from a target or surface, it must reside on a stable platform away from the target or surface being observed. Platforms for remote sensors may be situated on the ground, on an aircraft, or balloon (or some other platform within the earth’s atmosphere), or on a spacecraft or satellite outside the earth’s atmosphere.
Ground-based sensors are often used to record detailed information about the surface that is compared with information collected from aircraft or satellite sensors. In some cases, this can be used to better characterize the target that is being imaged by these other sensors, making it possible to better understand the information in the imagery. Sensors may be placed on a ladder, scaffolding, tall building, cherry-picker, crane, etc.
However, remotely sensed data are mainly collected either from the platforms within the earth’s atmosphere (air), or platforms in the space (outside of earth’s atmosphere). Platforms within the air are called aerial or airborne platforms, and platforms in the space are called space-borne or space platforms. Accordingly remote sensing is also referred as aerial or airborne or sub-orbital remote sensing, and space or space-borne or orbital remote sensing.
Different aerial platforms are balloons, kites, pigeons, aircrafts, etc. Balloons, kites, and pigeons are the early platforms of remote sensing and currently not used. Aircrafts are the main aerial platforms. An aircraft is a vehicle which is able to fly by being supported by the air. In remote sensing, aircrafts are primarily stable wing aeroplanes, although helicopters are also occasionally used.
In space, remote sensing is conducted mainly from satellites, and it is called satellite remote sensing. It is also known as satellite-borne remote sensing. Satellites are objects which revolve around another object--in this case, the earth. For instance, the moon is a natural satellite, whereas man-made satellites include platforms that are launched for remote sensing, communication, and telemetry (location and navigation) purposes.
Remote sensing, in space, may also be performed from space stations (such as, International Space Station); however it is a rare case. Other rarely used sensor platform is space transport system, commonly known as space shuttle. Data acquired from space station and space shuttle are used for scientific experimentations; they are not available commercially or widely.
Cost is often a significant factor in choosing among the various platform options. Moreover, each of the platforms has its own advantages and disadvantages. Satellite remote sensing can significantly enhance the information available from traditional data sources because it can provide synoptic view of large portions of the earth. Satellite imagery can also expand the spatial dimensions of limited and sometimes costly field or point-source sampling efforts. Some satellite sensors cover areas that may be physically or politically inaccessible, or that are too vast to survey with traditional methods. Satellite remote sensing can also provide consistent repeat coverage at relatively frequent intervals, making detection and monitoring of change feasible. Satellite-derived data and information are also useful for applications that require fine spatial resolution such as surveys of urban and suburban land-use/land-cover, for agricultural purposes, and natural resources; surveys for coastal management; and measurements of water quality in limnological (concerning lake and other fresh waters) and oceanographic applications.
The disadvantages of satellite remote sensing include the inability of many sensors to obtain data and information through cloud cover (although microwave sensors can image the earth through clouds) and the relatively low spatial resolution achievable with many satellite-borne earth remote sensing instruments.
In addition, the need to correct for atmospheric absorption and scattering, and for the absorption of radiation through water on the ground can make it difficult to obtain desired data and information on particular variables. Satellite remote sensing creates large quantities of data that typically require extensive processing as well as storage and analysis.
Finally, data from satellite remote sensing are often costly if purchased from private vendors or value-adding resellers, and this initial cost, together with intellectual property restrictions, can limit the dissemination of products from such sources.
In many instances, there may be an advantage of combining the large-scale, synoptic data that are accessible from space with higher-resolution surveys of key locations that can be made from other platforms, such as aircraft. Aerial photography, for instance, has a competitive advantage in applications that require fine spatial resolution of small areas or that involve areas subject to frequent cloud cover, especially in cases where repeat coverage is not needed (mobilizing the aircraft repeatedly will be a costly process). Another advantage of aerial photography is that surveys can be scheduled for specific purposes, time, and locations. But aircraft cannot be mobilized in politically inaccessible areas.
Classification Based on Energy Source
As we know the sun is the natural source of energy or radiation. The sun provides a very suitable source of energy for remote sensing. This energy is either reflected, as it is for visible and reflective IR wavelengths, or absorbed and then reemitted, as it is for thermal infrared wavelengths. Remote sensing systems which measure energy that is naturally available are called passive remote sensing. Passive sensors can only be used to detect naturally occurring energy. Passive remote sensing can only take place during the time when the sun is illuminating the earth, because the sun is the natural source of energy. There is no reflected energy available from the sun at night. Energy which is naturally emitted (such as thermal infrared) can be detected day or night, as long as the amount of energy is large enough to be recorded.
Active sensors, on the other hand, provide their own energy source for illumination. The sensor emits radiation, which is directed towards the target to be investigated. The radiation reflected from that target is then detected and measured by the sensor. Advantages for active sensors include the ability to obtain measurements anytime, regardless of the time of the day or season. Active sensors can be used for examining wavelengths that are not sufficiently provided by the sun, such as microwaves, or to better control the way a target is illuminated. However, active systems require the generation of a fairly large amount of energy to adequately illuminate targets. A laser fluorosensor and synthetic aperture radar (SAR) are some examples of active sensors.
Classification Based on Imaging Media
Reflected or emitted energy from terrain may be imaged, either photographically or electronically (digitally). The photographic imaging process uses chemical reactions on the surface of light-sensitive film to detect and record energy variations. In the case of digital imaging, sensors use electronic transducers such as charge coupled devices (CCDs).
Since its inception, photographic imaging system for remote sensing has been widely used from aerial platforms. Other platforms like space shuttle and early experimental spacecrafts had also been used for photographic imaging on experimental basis. However, in applied remote sensing, these platforms do not have any significance and aeroplane is the only platform used for photographic imaging. Digital imaging is rather a new technique that is being used from satellites as well as aeroplanes. Important to realize that satellite remote sensing is based on digital imaging; because a satellite remains on its orbit throughout its life and there is no chance of getting the film if recorded photographically. Digitally recorded data are transmitted from the satellite to the earth via digital communication link.
Photographic remote sensing is possible only within the range of photographic region (i.e. 0.3–0.9 micrometer) of electromagnetic spectrum. Therefore, digital imaging is the only choice if the sensor uses wavelengths that are outside of this region. Digital technique is capable of much higher spectral resolution than photographic systems. Multi-band or multispectral photographic systems use separate lens systems to acquire each spectral band. This may lead to problems in ensuring that the different bands are comparable both spatially and radiometrically and with registration of the multiple images. Digital systems acquire all spectral bands simultaneously through the same optical system to alleviate these problems. Photographic systems record the energy detected by means of a photochemical process, which is difficult to measure, and to maintain consistency. Because digital image data are recorded electronically, it is easier to determine the specific amount of energy measured, and they can record over a greater range of values. Photographic systems require a continuous supply of film and processing on the ground after the photos have been taken. The digital recording systems facilitate transmission of data to receiving stations on the ground and immediate processing of data in a computer environment.
Classification Based on the Regions of Electromagnetic Spectrum
As discussed in Chapter 1, remote sensing may be performed in different regions of electromagnetic spectrum. Remote sensing can also be classified based on the regions of electromagnetic spectrum in use. Optical remote sensing is performed within the optical region (0.3–3.0 micrometer), photographic remote sensing is performed within the photographic region (0.3–0.9 micrometer), thermal remote sensing uses the thermal region (3.0 micrometer – 1 mm), and microwave remote sensing is conducted within the microwave region (1 mm – 1 m). Optical and photographic remote sensing records reflected energy from the earth’s surface. These sensors generally use the sun as a source of energy (an exception is LiDAR). Thermal and passive microwave remote sensing uses emitted energy from the earth’s surface. However, active microwave remote sensing throws artificially generated energy to the earth’s surface and then the backscattered energy is recorded by the sensor. Backscatter is the term given to reflections in the opposite direction to the incident active microwave rays.
Several other techniques, for example LiDAR and SONAR, are also available. However, these are not widely used and difficult to understand at this point of discussion. The use of different wavelengths (and thereby techniques) is mainly because of different applications.
Classification Based on Number of Bands
Images for a geographic area may be collected in single band or more than one bands. Remote sensing can also be classified based on the number of bands to which a sensor is sensitive.
Panchromatic remote sensing is defined as the collection of reflected, emitted, or backscattered energy from an object or area of interest in a single band of the electromagnetic spectrum. In this case, generally, images are collected within the visible region (i.e., 0.4–0.7 micrometer); however, in some of the instances a wider region is also used (e.g., 0.3–0.9 micrometer). Therefore, if a sensor captures images in single band in microwave region it can not be said as panchromatic image. It must use the visible region or a wider region that essentially contains visible region.
Multi-spectral remote sensing is defined as the collection of reflected, emitted, or backscattered energy from an object or area of interest in multiple bands of the electromagnetic spectrum. In order to increase the spectral discrimination, remote sensing systems designed to monitor the earth’s surface, employ a multi-spectral design. Multi-spectral sensors can detect energy in a less number of broad wavelength bands. Multi-spectral remote sensing may be performed in the optical, thermal, as well as microwave regions. However, sensors and imaging techniques are different for different regions.
Hyper-spectral remote sensing is a major advancement in remote sensing, which is currently coming into its own as a powerful and versatile means for continuous sampling of narrow intervals of the spectrum. It is, in many respects, just an extension of the techniques employed in multi-spectral remote sensing. Multi-spectral remote sensors produce images with a few relatively broad wavelength bands. Hyper-spectral remote sensors, on the other hand, collect image data simultaneously in dozens or hundreds of narrow (as little as 0.01 micrometer in width for each), adjacent spectral bands. Hyper-spectral remote sensing is generally performed within the optical and thermal region of electromagnetic spectrum.
Panchromatic remote sensing can be conducted either photographically or digitally. Similarly, multi-spectral remote sensing can also be conducted photographically or digitally if it is performed within the photographic region. However, if it includes wavelengths outside of the photographic region then it must use digital imaging. Multi-spectral remote sensing, nowadays, is conducted digitally. For the hyper-spectral remote sensing, digital technique is the only method; because, photographic film can not be used to capture such a narrow spectral band.
Remote sensing is a complex technique and may vary based on the application and technological development. Considering technological development, for example, in the earlier days remote sensing was performed from balloons, but nowadays satellites are being used. Earlier, photographic cameras remained the only option, but nowadays digital cameras/sensors are dominating. Considering applications, for example, mapping purposes can be fulfilled by optical images, but information about temperature needs thermal image.
Remote sensing may be classified from many perspectives, for example, based on platform, source of energy, number of bands, and so on. The following sections explain remote sensing from the perspective of different classification schemes.
Classification Based on Platform
In order for a remote sensor to collect and record energy reflected or emitted from a target or surface, it must reside on a stable platform away from the target or surface being observed. Platforms for remote sensors may be situated on the ground, on an aircraft, or balloon (or some other platform within the earth’s atmosphere), or on a spacecraft or satellite outside the earth’s atmosphere.
Ground-based sensors are often used to record detailed information about the surface that is compared with information collected from aircraft or satellite sensors. In some cases, this can be used to better characterize the target that is being imaged by these other sensors, making it possible to better understand the information in the imagery. Sensors may be placed on a ladder, scaffolding, tall building, cherry-picker, crane, etc.
However, remotely sensed data are mainly collected either from the platforms within the earth’s atmosphere (air), or platforms in the space (outside of earth’s atmosphere). Platforms within the air are called aerial or airborne platforms, and platforms in the space are called space-borne or space platforms. Accordingly remote sensing is also referred as aerial or airborne or sub-orbital remote sensing, and space or space-borne or orbital remote sensing.
Different aerial platforms are balloons, kites, pigeons, aircrafts, etc. Balloons, kites, and pigeons are the early platforms of remote sensing and currently not used. Aircrafts are the main aerial platforms. An aircraft is a vehicle which is able to fly by being supported by the air. In remote sensing, aircrafts are primarily stable wing aeroplanes, although helicopters are also occasionally used.
In space, remote sensing is conducted mainly from satellites, and it is called satellite remote sensing. It is also known as satellite-borne remote sensing. Satellites are objects which revolve around another object--in this case, the earth. For instance, the moon is a natural satellite, whereas man-made satellites include platforms that are launched for remote sensing, communication, and telemetry (location and navigation) purposes.
Remote sensing, in space, may also be performed from space stations (such as, International Space Station); however it is a rare case. Other rarely used sensor platform is space transport system, commonly known as space shuttle. Data acquired from space station and space shuttle are used for scientific experimentations; they are not available commercially or widely.
Cost is often a significant factor in choosing among the various platform options. Moreover, each of the platforms has its own advantages and disadvantages. Satellite remote sensing can significantly enhance the information available from traditional data sources because it can provide synoptic view of large portions of the earth. Satellite imagery can also expand the spatial dimensions of limited and sometimes costly field or point-source sampling efforts. Some satellite sensors cover areas that may be physically or politically inaccessible, or that are too vast to survey with traditional methods. Satellite remote sensing can also provide consistent repeat coverage at relatively frequent intervals, making detection and monitoring of change feasible. Satellite-derived data and information are also useful for applications that require fine spatial resolution such as surveys of urban and suburban land-use/land-cover, for agricultural purposes, and natural resources; surveys for coastal management; and measurements of water quality in limnological (concerning lake and other fresh waters) and oceanographic applications.
The disadvantages of satellite remote sensing include the inability of many sensors to obtain data and information through cloud cover (although microwave sensors can image the earth through clouds) and the relatively low spatial resolution achievable with many satellite-borne earth remote sensing instruments.
In addition, the need to correct for atmospheric absorption and scattering, and for the absorption of radiation through water on the ground can make it difficult to obtain desired data and information on particular variables. Satellite remote sensing creates large quantities of data that typically require extensive processing as well as storage and analysis.
Finally, data from satellite remote sensing are often costly if purchased from private vendors or value-adding resellers, and this initial cost, together with intellectual property restrictions, can limit the dissemination of products from such sources.
In many instances, there may be an advantage of combining the large-scale, synoptic data that are accessible from space with higher-resolution surveys of key locations that can be made from other platforms, such as aircraft. Aerial photography, for instance, has a competitive advantage in applications that require fine spatial resolution of small areas or that involve areas subject to frequent cloud cover, especially in cases where repeat coverage is not needed (mobilizing the aircraft repeatedly will be a costly process). Another advantage of aerial photography is that surveys can be scheduled for specific purposes, time, and locations. But aircraft cannot be mobilized in politically inaccessible areas.
Classification Based on Energy Source
As we know the sun is the natural source of energy or radiation. The sun provides a very suitable source of energy for remote sensing. This energy is either reflected, as it is for visible and reflective IR wavelengths, or absorbed and then reemitted, as it is for thermal infrared wavelengths. Remote sensing systems which measure energy that is naturally available are called passive remote sensing. Passive sensors can only be used to detect naturally occurring energy. Passive remote sensing can only take place during the time when the sun is illuminating the earth, because the sun is the natural source of energy. There is no reflected energy available from the sun at night. Energy which is naturally emitted (such as thermal infrared) can be detected day or night, as long as the amount of energy is large enough to be recorded.
Active sensors, on the other hand, provide their own energy source for illumination. The sensor emits radiation, which is directed towards the target to be investigated. The radiation reflected from that target is then detected and measured by the sensor. Advantages for active sensors include the ability to obtain measurements anytime, regardless of the time of the day or season. Active sensors can be used for examining wavelengths that are not sufficiently provided by the sun, such as microwaves, or to better control the way a target is illuminated. However, active systems require the generation of a fairly large amount of energy to adequately illuminate targets. A laser fluorosensor and synthetic aperture radar (SAR) are some examples of active sensors.
Classification Based on Imaging Media
Reflected or emitted energy from terrain may be imaged, either photographically or electronically (digitally). The photographic imaging process uses chemical reactions on the surface of light-sensitive film to detect and record energy variations. In the case of digital imaging, sensors use electronic transducers such as charge coupled devices (CCDs).
Since its inception, photographic imaging system for remote sensing has been widely used from aerial platforms. Other platforms like space shuttle and early experimental spacecrafts had also been used for photographic imaging on experimental basis. However, in applied remote sensing, these platforms do not have any significance and aeroplane is the only platform used for photographic imaging. Digital imaging is rather a new technique that is being used from satellites as well as aeroplanes. Important to realize that satellite remote sensing is based on digital imaging; because a satellite remains on its orbit throughout its life and there is no chance of getting the film if recorded photographically. Digitally recorded data are transmitted from the satellite to the earth via digital communication link.
Photographic remote sensing is possible only within the range of photographic region (i.e. 0.3–0.9 micrometer) of electromagnetic spectrum. Therefore, digital imaging is the only choice if the sensor uses wavelengths that are outside of this region. Digital technique is capable of much higher spectral resolution than photographic systems. Multi-band or multispectral photographic systems use separate lens systems to acquire each spectral band. This may lead to problems in ensuring that the different bands are comparable both spatially and radiometrically and with registration of the multiple images. Digital systems acquire all spectral bands simultaneously through the same optical system to alleviate these problems. Photographic systems record the energy detected by means of a photochemical process, which is difficult to measure, and to maintain consistency. Because digital image data are recorded electronically, it is easier to determine the specific amount of energy measured, and they can record over a greater range of values. Photographic systems require a continuous supply of film and processing on the ground after the photos have been taken. The digital recording systems facilitate transmission of data to receiving stations on the ground and immediate processing of data in a computer environment.
Classification Based on the Regions of Electromagnetic Spectrum
As discussed in Chapter 1, remote sensing may be performed in different regions of electromagnetic spectrum. Remote sensing can also be classified based on the regions of electromagnetic spectrum in use. Optical remote sensing is performed within the optical region (0.3–3.0 micrometer), photographic remote sensing is performed within the photographic region (0.3–0.9 micrometer), thermal remote sensing uses the thermal region (3.0 micrometer – 1 mm), and microwave remote sensing is conducted within the microwave region (1 mm – 1 m). Optical and photographic remote sensing records reflected energy from the earth’s surface. These sensors generally use the sun as a source of energy (an exception is LiDAR). Thermal and passive microwave remote sensing uses emitted energy from the earth’s surface. However, active microwave remote sensing throws artificially generated energy to the earth’s surface and then the backscattered energy is recorded by the sensor. Backscatter is the term given to reflections in the opposite direction to the incident active microwave rays.
Several other techniques, for example LiDAR and SONAR, are also available. However, these are not widely used and difficult to understand at this point of discussion. The use of different wavelengths (and thereby techniques) is mainly because of different applications.
Classification Based on Number of Bands
Images for a geographic area may be collected in single band or more than one bands. Remote sensing can also be classified based on the number of bands to which a sensor is sensitive.
Panchromatic remote sensing is defined as the collection of reflected, emitted, or backscattered energy from an object or area of interest in a single band of the electromagnetic spectrum. In this case, generally, images are collected within the visible region (i.e., 0.4–0.7 micrometer); however, in some of the instances a wider region is also used (e.g., 0.3–0.9 micrometer). Therefore, if a sensor captures images in single band in microwave region it can not be said as panchromatic image. It must use the visible region or a wider region that essentially contains visible region.
Multi-spectral remote sensing is defined as the collection of reflected, emitted, or backscattered energy from an object or area of interest in multiple bands of the electromagnetic spectrum. In order to increase the spectral discrimination, remote sensing systems designed to monitor the earth’s surface, employ a multi-spectral design. Multi-spectral sensors can detect energy in a less number of broad wavelength bands. Multi-spectral remote sensing may be performed in the optical, thermal, as well as microwave regions. However, sensors and imaging techniques are different for different regions.
Hyper-spectral remote sensing is a major advancement in remote sensing, which is currently coming into its own as a powerful and versatile means for continuous sampling of narrow intervals of the spectrum. It is, in many respects, just an extension of the techniques employed in multi-spectral remote sensing. Multi-spectral remote sensors produce images with a few relatively broad wavelength bands. Hyper-spectral remote sensors, on the other hand, collect image data simultaneously in dozens or hundreds of narrow (as little as 0.01 micrometer in width for each), adjacent spectral bands. Hyper-spectral remote sensing is generally performed within the optical and thermal region of electromagnetic spectrum.
Panchromatic remote sensing can be conducted either photographically or digitally. Similarly, multi-spectral remote sensing can also be conducted photographically or digitally if it is performed within the photographic region. However, if it includes wavelengths outside of the photographic region then it must use digital imaging. Multi-spectral remote sensing, nowadays, is conducted digitally. For the hyper-spectral remote sensing, digital technique is the only method; because, photographic film can not be used to capture such a narrow spectral band.
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