Types of Remote Sensing with Respect to Wavelength Regions
With respect to the wavelength regions of the electromagnetic spectrum used, remote sensing is classified into three types
as shown in Figure 1.5.1.
The energy source used in the visible and reflective infrared remote sensing is the sun. The sun radiates electro-magnetic energy with a peak wavelength of 0.5 m (see 1.7 and 1.10). Remote sensing data obtained in the visible and reflective infrared regions mainly depends on the reflectance of objects on the ground surface (see 1.8). Therefore, information about objects can be obtained from the spectral reflectance. However laser radar is exceptional because it does not use the solar energy but the laser energy of the sensor.
The source of radiant energy used in thermal infrared remote sensing is the object itself, because any object with a normal temperature will emit electro-magnetic radiation with a peak at about 10 m (see 1.7), as illustrated in Figure 1.5.1.
One can compare the difference of spectral radiance between the sun (a) and an object with normal earth temperature (about 300K), as shown in Figure 1.5.1. However it should be noted that the figure neglects atmospheric absorption (see 1.11), for simplification, though the spectral curve varies with respect to the reflectance, emittance and temperature of the object.
The curves of (a) and (b) cross at about 3.0 m. Therefore in the wavelength region shorter than 3.0 m, spectral reflectance is mainly observed, while in the region longer than 3.0 m, thermal radiation is measured.
In the microwave region, there are two types of micro wave remote sensing, passive microwave remote sensing and active remote sensing. In passive microwave remote sensing, the microwave radiationemitted from an object is detected, while the back scattering coefficient is detected in active micro wave remote sensing. (see 3.4).
Remarks: the two curves (a) and (b) in Figure 1.5.1 show the black body's spectral radiances of the sun at a temperature of 6,000K and an object with a temperature of 300K, without atmospheric absorption.
Electromagnetic radiation reveals its presence by the observable effects it produces when it interacts with matter. The energy source used in much of remote sensing, viz., the visible and reflective infrared remote sensing is the sun. The sun radiates electro-magnetic energy with a peak wavelength of 0.5 μm. Remote sensing data obtained in the visible and reflective infrared regions mainly depends on the reflectance of objects on the ground surface. Therefore, information about objects can be obtained from the spectral reflectance. Optical remote sensing devices operate in the visible, near infrared, middle infrared and short wave infrared portion of the electromagnetic spectrum. These devices are sensitive to the wavelengths ranging from 300 nm to 3000 nm. Most of the remote sensors record the EMR in this range, e.g., bands of IRS P6 LISS IV sensor are in optical range of EMR.
The electromagnetic spectrum ranges from the very short wavelengths of the gamma-ray region (measured in fractions of nanometers) to the long wavelengths of the radio region (measured in meters). This is divided on the basis of wavelength into regions that are described in Table 1. Fig 1 shows the various regions. It may be noticed that the visible region (0.4 to 0.7 µm wavelengths) occupies only a small portion of the spectrum. Energy reflected from the earth during daytime may be recorded as a function of wavelength. The maximum amount of energy is reflected at 0.5 µm wavelength, which corresponds to the green band of the visible region, and is called the reflected energy peak. The earth also radiates energy both day and night, with the maximum energy radiating at 9.7 µm wavelength. This radiant energy peak occurs in the thermal band of the IR region (Fig 1)
Fig 1. Wavelength regions of the electromagnetic spectrum.
The earth's atmosphere absorbs energy in the gamma-ray, X-ray, and most of the ultraviolet (UV) region; therefore, these regions are not used for remote sensing. Sensors record energy in the visible & near infrared, reflected infrared, thermal infrared and microwave regions.
Remote sensing is classified into four types with respect to the wavelength regions; (1) Visible and Reflective Infrared Remote Sensing, (2) Short-wave infrared, (3) Thermal Infrared Remote Sensing and (4) Microwave Remote Sensing.
Visible and Near-Infrared (VNIR) Remote Sensing
VNIR stands for visible and near-infrared, a portion of the electromagnetic spectrum having wavelengths between approximately 400 and 1400 nm. It combines the full visible spectrum with an adjacent portion of the infrared spectrum up to the water absorption band between 1400 and 1500 nm. Some definitions also include the short-wavelength infrared band from 1400nm up to the water absorption band at 2500nm. VNIR multi-spectral image cameras have wide applications in remote sensing and imaging spectroscopy.
From a geologic point of view, the VNIR region of remote sensing is important. Absorption bands due to ferrous iron in pyroxenes, iron in amphiboles and iron in siderite and manganese in rhodochrosite occur in the VNIR region.
The VNIR region is split into a number of bands, each of which is useful in distinguishing land cove features. The following is just a guide based on LISS 3/4 and LANDSAT Bands 1-4.
Band 1 (0.45-0.52 µm): coastal water mapping, soil/vegetation discrimination, forest classification, man-made feature identification.
Band 2 (0.52-0.60 µm): vegetation discrimination and health monitoring, man-made feature identification.
Band 3 (0.63-0.69 µm): plant species identification, man-made feature identification.
Band 4(0.76-0.90 µm): soil moisture monitoring, vegetation monitoring, water body discrimination
Short-Wave Infrared (SWIR) Remote Sensing
The short wave infrared remote sensing region utilizes the reflected wavelength range from 1.0 to 3.0 μm. The reflectance of vegetation in the SWIR region (e.g. band 5 of Landsat TM and band 4 of SPOT 4 sensors) is more varied, depending on the types of plants and the plant's water content. Water has strong absorption bands around 1.45, 1.95 and 2.50 µm. Outside these absorption bands in the SWIR region, reflectance of leaves generally increases when leaf liquid water content decreases. This property can be used for identifying tree types and plant conditions from remote sensing images. The SWIR band can be used in detecting plant drought stress and delineating burnt areas and fire-affected vegetation. The SWIR band is also sensitive to the thermal radiation emitted by intense fires, and hence can be used to detect active fires, especially during night-time when the background interference from SWIR in reflected sunlight is absent.
Thermal Infrared (TIR) remote Sensing
Thermal infrared remote sensing utilizes the EMR region ranging from 3 to 5 μm and 8 to 14 μm. The wavelength region between 5 and 8 μm is strongly absorbed by water in the earth’s atmosphere. The TIR range is related to high temperature phenomenon like forest fire, and later with the general earth features having lower temperatures. Hence thermal remote sensing is very useful for fire detection and thermal pollution.
Thermal infrared remote sensing is finding use in landscape ecology studies. The primary use on TIR data in mountainous areas has been for mapping of geological formations. Despite the difficulties in working in mountainous environments, the potential of using TIR remote sensing data is high since it can provide important new information in the analysis and modeling of landscape ecological phenomena. The TIR remote sensing data are particularly useful for understanding the fluxes and redistribution of materials among landscape elements. Thus the observation, measurement and analysis of thermal fluxes, as they contribute to energy balance characteristics, is an implicit and important aspect of landscape dynamics and landscape functioning in mountainous terrains. TIR data are also useful in measuring evapotranspiration and soil moisture. Procedures to convert digital values on a TIR image to spectral radiance are established. Once the radiant temperature is known, the kinetic temperatures are estimated. TM bands 7 and 5 can be together used to measure pixel-integrated temperatures from 160°C to 420°C. Sea surface temperatures are derived from radiometric observations at wavelengths of ~3.7 µm and/or near 10 µm. Bands 10-14 of ASTER and band 6 of Landsat ETM+ operates in thermal range.
For more details of infrared remote sensing see the article: http://en.wikipedia.org/wiki/Infrared
Microwave Remote Sensing
In the microwave region, there are two types of micro wave remote sensing, passive microwave remote sensing and active remote sensing. In passive microwave remote sensing, the microwave radiation emitted from an object is detected, while in active microwave remote sensing, the back scattering coefficient is detected.
Passive Microwave Remote Sensing
Objects at the earth’s surface emit not only infrared radiation; they also emit microwaves at relatively low energy levels. When a sensor detects microwave radiation naturally emitted by the earth, that radiation is called passive microwave. Clouds do not emit much microwave radiation, compared to sea ice. Thus, microwaves can penetrate clouds and be used to detect sea ice during the day and night, regardless of cloud cover.
Microwave emission is not as strongly tied to the temperature of an object, compared to infrared. Instead, the object’s physical properties, such as atomic composition and crystalline structure, determine the amount of microwave radiation it emits. The crystalline structure of ice typically emits more microwave energy than the liquid water in the ocean. Thus, sensors that detect passive microwave radiation can easily distinguish sea ice from ocean.
A major drawback to measuring passive microwave radiation is that the energy level is quite low. As a result, the radiation must be collected over a larger region. Details of the sea ice, such as leads, are not easily detected.
Because of their ability to detect sea ice through clouds during the day and night, passive microwave sensors provide nearly complete images of all sea ice-covered regions every day. These sensors have provided the most complete, long-term observations of sea ice, allowing scientists to detect notable changes in Arctic sea ice.
Sea ice observations from passive microwave sensors began in 1972 with the Electrically Scanning Microwave Radiometer (ESMR) aboard NOAA’s Nimbus-5 satellite. In 1978, NASA’s Scanning Multichannel Microwave Radiometer (SMMR) provided detailed, reliable information about sea ice. In 1987, a series of DMSP Special Sensor Microwave/Imager (SSM/I) sensors continued the time series, or long-term record, of sea ice data through present. In 2002, NASA launched the Aqua satellite, which carried the Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) sensor. The system's improved technology complemented the time series of sea ice data. ESMR, SMMR, SSM/I, and AMSR-E sea ice data are available from NSIDC.
Active Microwave Remote Sensing:
Although radar technology and active microwave remote sensing has been available for more than 50 years, it has not been put to use on a scale to which optical remote sensing has been used. Despite the sound theoretical principles of its utility in urban/suburban and natural environments, there has been a paucity of applications of active radar in land-cover and land-use monitoring. This may be attributed to a lack of general understanding of radar data and to insufficient methods of analyzing them. However, for the last 20 years a number of synthetic aperture radar (SAR) systems have been developed, and five separate spaceborne SAR systems have been successfully deployed: SIR-C/X-SAR, ERS-1, ERS-2, JERS-1, and RADARSAT-1.
Of these, only RADARSAT-1 (launched by the Canadian government in 1995) and ERS-2 (launched by the European Space Agency in 1995) are still in continuous operation. C-band RADARSAT-1 is unique in that it provides a range of spatial resolutions and geographic coverages. For example, in Fine Beam mode, data are acquired over 50 X 50 km2 areas at 10 m spatial resolution, whereas, in ScanSAR Wide Beam mode, data are acquired over 500 500 km2 areas at 100 m spatial resolution . ERS-2 collects data in C-band wavelengths at 26 X 30 m2 spatial resolution. C-band data from these sensors have been used effectively in a number of forest mapping and forest change detection studies. The remote sensing research community appears to have a better grasp of the potential of active SAR in natural environments, but work is continuing in urban/suburban environments, particularly around the synergistic application of SAR and optical data. Several new SAR satellites are planned for launch in the near future, adding polarization diversity and polarimetry to a range of resolutions and swath widths (e.g. ENVISAT, ALOS, PALSAR, and RADARSAT-2).
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