Sar Application For Vegetation Studies Biology Essay

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Remote sensing is the art or science of acquiring information about objects targets on the Earth's surface by using sensors mounted on platforms located at a distance from the targets. Measurements are made in different wavelength regions on interactions between the targets and electromagnetic radiation (EMR).

bThe EM spectrum covers various wavelengths/frequencies of electro-magnetic radiation from lowest frequencies (longest wavelengths), radio spectrum to highest frequencies, gamma rays. Remote sensing with respect to wavelength regions is also divided into two types: Optical and Radar remote sensing. The optical wavelength region (0.30-15.0 nm), is further subdivided as Visible (0.38-0.72nm), Near IR (0.72-1.30nm), Middle IR (1.30-3.00nm) and Far IR (7.00-15.0nm). Multi-spectral scanners which are operated in the visible and infrared regions of the spectrum are used extensively as remote sensing tools for a wide variety of applications.

The figure (b) illustrates the microwave portion of the spectrum. Microwave region extends from 0.3 to 300 GHz (1 m to 1 cm in wavelength). The different microwave regions are represented by letters and are indicated in the figure (b). The different frequency and wave length bands of microwave region are given in the below table:


Frequency (GHz)

Wavelength (cm)



















Types of Remote Sensing: With respect to the energy resources used, there are two types o remote sensing: Active and Passive. Active remote sensing detects reflected responses from objects that are irradiated from artificially generated energy sources. They provide their own illumination and hence comprises of a transmitter and a receiver (Radar imaging systems (RADAR: RAdio Detection And Ranging, Scatterometers, Altimeters) while Passive remote sensing detects the reflected or emitted electro-magnetic radiation from natural sources. Passive sensors are receivers that measure the radiation backscattered from the scene under observation (Microwave Radiometers). Radar systems are commonly based on the measurement of signal time delays.


The basic principle of radar is transmission and reception of pulses. Short high-energy pulses are emitted by the transmitter and the returning echoes are recorded by the receiver. It provides information on magnitude, phase, time interval between pulse emission and return from the object, polarization and Doppler frequency.

A short pulse is transmitted from the radar and when the pulse strikes a target, a signal returns to the antenna. The time delay between the signal transmitted and the signal received gives the distance between target and sensor. As the speed of light at which the pulse propagates is much faster than the platform velocity, the echo of the pulse from the ground is assumed to be received at the same spacecraft position at which the pulse was transmitted.

Imaging radars used for remote sensing are side-looking airborne radars (SLARs). A platform carries a side looking antenna perpendicular to the flight direction of the platform and transmits radar pulses in a direction different from the flight path. As the platform moves one beam width forward, the return signals come from a different strip on the ground. These signals intensity-modulate the line on the cathode-ray tube and produce a different image on a line on the film adjacent to the original line. As the platform moves forward, a series of these lines is imaged onto the film, and the result is a two-dimensional picture of the radar return from the surface.

The area continuously imaged from the radar beam is called the swath and can be divided into near range and far range. Each transmitted wave front hits the target surface at near range and sweeps across the swath to far range.

Slant range and Ground range:

Distance from the radar to the scatterer is called range. As the radar is located at some altitude above the ground, this is not same as distance along the ground. Thus, the dimension in the image is called slant range.

The figure shows two types of radar data display: - slant range image, in which distances are measured between the antenna and the target. Slant range data is the natural result of radar range measurements. A slant range coordinate is defined in a direction normal to the flight path and an azimuth coordinate is defined in the direction along the flight path. In Ground range image, distances are measured between the platform ground track and the target, and placed in the correct position on the chosen reference plane. Transformation to ground range requires correction at each data point for local terrain slope and elevation. Ground range resolution (Rr) is the horizontal expression of the slant range resolution and is expressed mathematically as:

θD is the depression angle and t is the pulse duration.

The differences between the many imaging radars used in remote sensing are primarily due to the antenna which determines the spatial resolution in the azimuth direction (Raney 1998). Imaging radars can be divided in two main categories, depending on the imaging technique used: Real Aperture Radar (RAR) also called Side Looking Airborne Radar (SLAR) and the Synthetic Aperture Radar (SAR).

Both SLAR and SAR are side-looking systems with an illumination direction usually perpendicular to the flight line. The difference lies in the resolution of the along-track, or azimuth direction. SLAR have azimuth resolution determined by the antenna beamwidth, so that it is proportional to the distance between the radar and the target (slant-range).

SAR improves natural radar resolution by focusing the image through a process known as synthetic aperture processing which synthesizes a very long antenna by combining signals (echoes) received by the radar as it moves along its flight track. A synthetic aperture is constructed by moving a real aperture or antenna through a series of positions along the flight track. These systems have azimuth resolution (along-track resolution) that is independent of the distance between the antenna and the target. SAR takes advantage of Doppler's history of the radar echoes generated by the forward motion of the platform to synthesize a large antenna, enabling high azimuth resolution in the resulting image despite a physically small antenna.

SAR works on the principle of Doppler Effect, a property of waves reflected (or emitted) by moving objects. If a wave is reflected or emitted by an object approaching a receiver, its frequency as observed by the receiver is increased; if the object is receding, its frequency as observed by the receiver is decreased. A narrow radar beam is projected at right angles to the forward motion of a platform. Distant objects moves across this side-looking beam as the aircraft moves in a straight line. As an object first enters the beam, its relative motion has a component that is toward the platform and which Doppler-shifts its RADAR reflection to higher frequencies. As the object passes through the centerline of the beam, it ceases to get closer to the aircraft. At this fraction of a second, its reflection ceases to be Doppler shifted. Next, as the object passes through the trailing half of the beam, it begins to move away from the aircraft, which Doppler-shifts its reflection to lower frequencies. Thus, although reflections from all objects at a given distance from the RADAR return to its antenna at the same moment, reflections from objects ahead of the aircraft are Doppler shifted to higher frequencies, and those from objects trailing the aircraft are shifted to lower frequencies. This effect can be used to distinguish objects inside the beam, achieving an angular resolution that is higher than the beam's physical width.

Comparing the Doppler-shifted frequencies to a reference frequency allows many returned signals to be "focused" on a single point, effectively increasing the length of the antenna that is imaging at that particular point. The result is a very narrow effective antenna beam width, even at far ranges without requiring long antenna or short operating wavelength. Within the wide antenna beam, returns from features in the area ahead of the aircraft will have up shifted frequencies resulting from Doppler Effect. Returns from features in the area behind the aircraft will have down shifted frequencies. Returns from features near the centre line of beam width have less or no frequency shift.

This aperture synthesis is achieved by coherently integrating the returned signal pulse-to-pulse as the radar moves along its path. The azimuth resolution attained in this manner is half a wavelength divided by the change in viewing angle during the aperture formation process.

Interpreting radar data depends on an understanding of the interaction between system parameters and target characteristics. Both RAR and SAR systems have specific operational parameters which will influence the interaction between the pulses transmitted and the targets on the Earth's surface.


Wavelength: As discussed above, the electromagnetic spectrum (refer 1st Fig) illustrates wide range of microwave wavelengths/frequencies. The interaction of microwaves and targets on Earth's land surface is dependent on the wavelength used. Penetration depth increases with the wavelength (Elachi 1988). The roughness of a surface on a SAR image is also influenced by the wavelength used.


The temporal and geometric behaviour of the electric field vector of an electromagnetic wave transmitted or received by a radar system is the polarization. It refers to the geometry of the tip of the electric vector (E) as it evolves with time. Remote sensing radars are usually designed to transmit either vertically polarized or horizontally polarized radiation and the radar can receive either vertically or horizontally polarized radiation, or both. The letters H and V designates the planes of transmitted and received polarization for Horizontal and Vertical. Therefore, the polarization of a radar image is HH, for horizontal transmit, horizontal receive, VV for vertical transmit, vertical receive, HV for horizontal transmit vertical receive, and vice versa. When the polarization of the received radiation is the same as the transmitted radiation, the image is said to be like polarized or co-polarized. When the polarization of the received radiation is orthogonal to the transmitted radiation, the image is said to be cross-polarized. Cross-polarized signals are usually a result of multiple scattering by the target or terrain. They are weaker than the co-polarized. The backscatter of microwaves from an object depends on polarization of the incident wave and also the geometric structure of the object.

A radar system which can record two different polarizations i.e., Orthogonal polarizations is a dual polarization Radar. Radar that is capable of acquiring more than one independent polarization measurement, either simultaneously or separately is Multi-polarization Radar. A multi-polarization radar system can have two to four possible polarizations and are not phase coherent. Multi-polarization radar may have only one channel, which acts as a switch between different polarizations. Radar systems designed to collect image data of a scene using two orthogonal transmit polarizations and the same two polarizations on receive is Quadrature polarization or Polarimetric Radar. The detailed explanation of polarimetry is given in Chapter 8. Transmit and receive channels are in orthogonal, and four channels are required to make the measurements (typically HH, HV, VV & VH).

Targets on the Earth's surface scatter microwave radiation differently depending on the polarization of the wave transmitted. If the plane of polarization of the transmitted wave is parallel to the main line of polarization of the target being sensed the like polarized backscatter is stronger. The cross-polarization or depolarization of the transmitted wave is also a function of the amount of multiple volumetric scattering taking place at the targets. SAR systems with cross-polarised receiving capabilities can provide additional information for the image interpretation and understanding the target/wave interaction (Lewis and Anderson 1998).

Incident angle: The incident angle (θ) is a major factor influencing the radar backscatter and the appearance of the targets in the images. This angle is defined between the radar pulse and a line perpendicular to the Earth's land surface. Figure 2.2 illustrates the system and local incident angles. In a flat surface, θ is the complement of the depression angle (γ) (Jensen 2000). Smaller incidence angle results in larger backscatter value.

In general, images acquired at small incident angles (less than 30°) emphasize variations in surface slope, and geometric distortions due to layover and foreshortening in mountainous regions can be severe. Images with large incident angles have reduced geometric distortion and emphasize variations in surface roughness, although radar shadows increase (Lillesand and Kiefer 2000).


The fundamental relation between the characteristics of the radar, the target, and the received signal is given by the radar equation. It predicts performance in terms of signal-to-interference ratio based upon the radar hardware, the distance to the target, the target's radar cross section, and the total system noise.

Five primary factors that determine signal strength are given in the radar equation: the density of radiated power at the range of the target; the radar reflectivity of the target and the spreading of radiation along the return path to the radar; the effective receiving area or aperture of the antenna; the time over which the target is illuminated; and signal losses caused by physical phenomena, such as conversion to heat, and processing losses.

The geometry of scattering from an isolated radar target (scatterer) is shown in the figure, with the parameters that are involved in the radar equation.

When a power Pt is transmitted by an antenna with gain Gt, the power per unit solid angle in the direction of the scatterer is PtGt, where the value of Gt in that direction is used. At the scatterer, -------------- (1)

where Ss is the power density at the scatterer. The spreading loss (1/4Ï€R2) is the reduction in power density associated with spreading of the power over a sphere of radius 'R' surrounding the antenna. Total power intercepted by the scatterer is obtained by the product of power density and effective receiving area of the scatterer:

'Ars' depends on the effectiveness of the scatterer as a receiving antenna.

As the scatterers are neither a perfect conductors nor perfect isolators, some of the power received by the scatterer is absorbed in losses and the rest is reradiated in various directions. The fraction absorbed is 'fa', so the fraction reradiated is '(1- fa)', and the total reradiated power is

----------- (7.2)

The conduction and displacement currents that flow in the scatterer result in reradiation that has a pattern. Effective receiving area of the scatterer is a function of its orientation relative to the incoming beam, so Ars in the equation is given for the direction of the incoming beam.

The reradiation pattern may not be the same as the pattern of 'Ars', and the gain in the direction of the receiver is the relevant value in the reradiation pattern. Thus,

---------- (7.3)

where Pts is the total reradiated power, Gts is the gain of the scatterer in the direction of the receiver, and (1/4Ï€R2) is the spreading factor for the reradiation. Radar has two spreading factors and if Rr = Rt, the total distance is 2Rt; Therefore, (1/4Ï€) 2 (1/Rt) 4

The power entering the receiver is given by;; where the area Ar is the effective aperture of the receiving antenna, not its actual area. Hence, the equation is

------------ (7.4)

The factors associated with the scatterer are combined in the square brackets.

These factors are difficult to measure individually, and hence they are normally combined into one factor, the radar scattering cross section:

------------ (7.5)

The cross-section, 'σ' is a function of the directions of the incident wave and the wave toward the receiver, as well as that of the scatterer shape and dielectric properties. The final form of the radar equation is obtained as

------------- (7.6)

If the receiving and transmitting locations are the same, the transmitter and receiver distances are the same. The same antenna is used for transmitting and receiving, so the gains and effective apertures are the same, that is:

Rt= Rr =R; Gt= Gr =G; At= Ar =A.

Since the effective area of an antenna is related to its gain by we may rewrite the radar equation as

---------- (7.7)

where two forms are given, one in terms of the antenna gain and the other in terms of the antenna area.

The targets scatter the energy transmitted by the radar in all directions. Radar records the energy scattered in the backward direction and is called backscatter. The intensity of each pixel in a radar image is proportional to the ratio between the density of energy scattered and the density of energy transmitted from the targets in the Earth's land surface (Waring et al. 1995).

The backscatter is measured as a complex number, which contains information about the amplitude (easily converted to σ° by specific equations) and the phase of the backscatter (Baltzer 2001). For SAR applications other than interferometry (detail explanation is given in Chapter-8) and polarimetry, however, the phase carries no useful information and can be discarded (Oliver and Quegan 1998). The information that remains when the phase is discarded is related to the amplitude of the backscatter. After linear detection and processing, amplitude SAR data are converted to an amplitude (or magnitude) image. After square-law detection and processing, amplitude SAR data are converted to an intensity (or power) image (Kingsley and Quegan 1992).

Backscatter co-efficient:

The energy backscattered is related to the variable referred as radar cross-section (σ), and is the amount of transmitted power absorbed and reflected by the target. The backscatter coefficient (σ°) is the amount of radar cross-section per unit area (A) on the ground (Jensen 2000).

σ° is a characteristic of the scattering behaviour of all targets within a pixel, varies over several orders of magnitude and is expressed as a logarithm with decibel units (Waring et al. 1995).

Backscatter coefficient is a function of wavelength, polarization and incidence angle, as well as target characteristics such as roughness, geometry and dielectric properties. The targets will be distinguishable in radar images if their backscatter components are different and the radar spatial resolution is adequate to discriminate between targets (Trevett, 1986).

RADAR Reflector Surfaces

RADAR reflectors represent the geometric orientation of the target that interacts with the radar pulse angle, pole and size. The reflectors can be described in 3 groups: specular, diffuse and corner or double-bounce. In general shrub and forest cover types and some crops represent diffuse reflectors where the RADAR pulse is diffused at different angles and some of the energy is directed back to the receiver thus the signal received is neither high nor low. A specular reflector is a mostly flat or non rough surface (calm water, grass field, bare soil, beach, etc.). The pulse hits the flat surface and most of the energy is directed out away from the surface at a right angle away from the receiver thus little energy is recorded. A corner reflector usually involves two adjacent surfaces (double bounce) and is a combination of a specular surface and a vertical object (e.g. trees) or a surface with strong angles such as a building. The RADAR pulse hits the specular surface first and the signal going out at a right angle (1st bounce) then interacts with a vertical or angular surface (2nd bounce) thus directing most or nearly all of the energy directly back to the receiver. This is the highest signal thus the object (tree or building in this case) would have a bright appearance on a SAR image.

Electrical characteristics

The electrical characteristics of targets also determine the intensity of backscatter. The complex dielectric constant is a measure of the electrical characteristics of objects, indicating the reflectivity and conductivity of various materials (Lillesand and Kiefer 2000). The moisture content within materials has a direct influence on the dielectric constant and reflectivity. The more liquid water within a material the more reflectivity/backscatter is produced (Waring et al. 1995). Most materials have a dielectric constant ranging from 3 to 8 when dry, while water has a dielectric constant of around 80. Forest canopies are excellent reflectors and appear bright in the image because of the leaves high moisture content, while dry soils absorb the radar signal and produce very low (or no) backscatter (Jensen 2000).



Speckle is due to the variation in backscatter for non-homogenous cells. It gives a grainy appearance to the Radar images. Speckle is caused by the high coherence of the illumination source that causes phase interference from random scattering points. The narrow bandwidth when combined with the surface roughness at the wavelength scale produces a pattern in grainy appearance. It is the unwanted and dominating noise. It degrades the SAR image products. Speckle is an undesirable feature containing little information. This is caused by random constructive and destructive interference from the multiple scattering returns that will occur within each resolution cell.

The salt-and-pepper texture of speckle is related to radar system parameters and the nature of the surface being imaged. The classical speckle model assumes the presence of a large number of independent point reflectors with similar scattering characteristics within the resolution cell. When illuminated by the SAR, each target contributes backscatter energy, which along with phase and power changes, is then coherently summed for all scatterers. This summation can be either high or low, depending on constructive or destructive interference. This statistical fluctuation (variance), or uncertainty, is associated with the brightness of each pixel in SAR imagery.

Speckle carries the information about the imaging system and is useful in describing the texture of image, identifying terrain features, examining the reflectivity and system transformation processes. Speckle is essentially a form of noise, which degrades the quality of an image and makes interpretation more difficult. Thus, it is generally desirable to reduce speckle prior to interpretation and analysis. Smoothening and Filtering are commonly used to reduce speckle. The speckle effect is reduced by using the multi look images and also by averaging the number of samples, increasing the time bandwidth products. Multi-look processing reduces speckle at the cost of spatial resolution. Filtering can reduce the speckle still inherent in the actual SAR image data, which tend to reduce statistical variance in conventional image classification schemes

Speckle reduction can be achieved in two ways:

Multi-look processing and

Spatial filtering.

Multi-look processing refers to the division of the radar beam into several narrower sub-beams. Each sub-beam provides an independent look at the illuminated scene, as the name suggests. Each of these looks will also be subject to speckle, but summing and averaging them together to form the final output image will reduce the amount of speckle. Multi-looking is done during data acquisition.

Speckle reduction by spatial filtering is performed on the output image in a digital image analysis environment. Speckle reduction filtering consists of moving a small window of a few pixels in dimension (e.g. 3x3 or 5x5) over each pixel in the image, applying a mathematical calculation using the pixel values within that window and replacing the central pixel with the new value. The window is moved along in both the row and column dimensions one pixel at a time, until the entire image has been covered. By calculating the average of a small window around each pixel, a smoothening effect is achieved and the visual appearance of the speckle is reduced.

Both multi-look processing and spatial filtering reduce speckle at the expense of resolution, since they both smoothens the image. Therefore, the amount of speckle reduction should be chosen based on user application and information required. If fine detail and high resolution is required then little or no multi-looking/spatial filtering should be done. If broad-scale interpretation and mapping is the application, then speckle reduction techniques may be more appropriate and acceptable. The speckle suppression techniques used in the present study are explained in Chapter 4.

Radar Image Distortions:

The Radar image obtained has distortions due to slant range geometry, topographic variations etc. These should be addressed and discussed for better understanding of SAR image processing.

Distortions in the Radar image are due to the side-looking viewing geometry and radar is a distance measuring system. Some of these distortions are Scale distortions and Relief distortions.

Scale distortion



A1 B1Slant-range scale distortion occurs because the radar is measuring the distance to features in slant-range rather than the true horizontal distance along the ground. This results in a varying image scale, moving from near to far range. The same distance on the ground the radar sees A1 and B1 as A2 and B2. The scale is shortened in the near range compared to the far range. Although targets A1 and B1 are the same size on the ground, their apparent dimensions in slant range A2 and B2 are different. This causes targets in the near range to appear compressed relative to the far range.

Relief Displacement: Radar images are subject to relief displacement. It is one-dimensional and occurs perpendicular to the flight path. The displacement is reversed with targets being displaced towards, instead of away from the sensor. Radar foreshortening and layover are two consequences that result from relief displacement. Taller objects may appear closer than shorter objects with the same horizontal locations.

Tall objects and very steep terrain can block the RADAR pulse from reaching the backside of the object (the geometry is called foreshortening or layover).

Foreshortening: It is a special case of elevation displacement. When the radar beam reaches the slope of a tall feature e.g. a mountain, at the same moment, the foreshortening will occur.

When the radar beam reaches the base of a tall feature tilted towards the radar, before it reaches the top, foreshortening will occur. As the radar measures distance in slant-range, the slope A to B will appear compressed and the length of the slope will be represented incorrectly A' to B'. Foreshortening depends on the angle of mountaintop with the angle of incidence of the Radar. Foreshortening is maximum when the radar beam is perpendicular to the slope, i.e., when the slope, base, and the top are imaged simultaneously.

Layover: Layover occurs when the radar beam reaches the top of a tall feature (B) before it reaches the base (A). The return signal from the top of the feature is received earlier than the signal from the bottom. As a result, the top of the feature is displaced towards the radar from its true position on the ground, and




Blays over the base of the feature B' to A'. Layover effects on a radar image look very similar to effects due to foreshortening. As with foreshortening, layover is most severe for small incidence angles, at the near range of a swath, and in mountainous terrain.

Radar Shadow occurs when the radar beam is not able to illuminate the ground surface. Both foreshortening and layover result in radar shadow. Shadows occur in the down range dimension (i.e. towards the far range), behind vertical features or slopes with steep sides. Since the radar beam does not illuminate the surface, shadowed regions will appear dark on an image, as no energy is available to be backscattered. As incidence angle increases from near to far range, shadow effects as the radar beam looks more and more obliquely at the surface. This image illustrates radar



Objectshadow effects on the right side of the hillsides that are being illuminated from the left. The null area is called a RADAR shadow and there is no return signal therefore the area and any lower lying objects in this zone of the image appear black on a image.

With these introduction to Radar image characteristics, we now discuss the Radar remote sensing of forests and its applications.

Radar remote sensing of forests:

Microwave remote sensing is very useful in the application of the forestry as the microwaves are capable of penetrating through the forest canopy and contribute to the monitoring of the forest and to understand the ecosystem processes.

Microwave radiation penetrates significant distances into a vegetation canopy and interacts most strongly with structures (leaves, stems etc) on scales comparable with the radiation's wavelength. Depending on wavelength and polarization, radar can penetrate the canopy to different depths (figure 2.2), and can sense plant parts of different sizes, shapes, and water content. This ability of radar to probe the canopy, and the expectation of retrieving biophysical forest descriptions, underlie much of the international impetus for forest radar research (Sun et al, 1998).

Microwave interaction depends on the angle of incidence and wavelength of the Radar. It is illustrated that there exists the relationship between the C, L, P-band radar backscatter and forest biomass and growing stock volume (Tansey et al.2004). Hence, these bands are used to retrieve the canopy biophysical parameters.

Radar remote sensing is also used to achieve biomass estimates and carbon accounting. Radar data also provides information about terrain surface and vegetation canopies (Heri et al, 1999). Synthetic Aperture Radar (SAR) provides important characteristics of soil and vegetation covers for instance, inundation below closed canopies, fresh woody biomass of forested areas, freeze/thaw conditions of soil and vegetation, soil moisture and surface roughness in areas of low vegetation, and information on the orientation and structure of objects on the ground that reflect the incoming microwave radiation (Kasischke et al., 1997; Morrissey et al. 1996).

Trees and other vegetation are usually moderately rough on the longer wavelength scale. Hence, they appear as moderately bright features in the image. Structures of trees affect the backscattering coefficient (Touzi et al, 2004). Backscattering and penetration varies within a forest canopy. In longer wavelengths, the effect of the trunk is very large. In shorter wavelengths, leaves play an important role in backscatter. This is due to the forest composition, tree density, and canopy thickness. The scattering properties are governed by size, shape and orientation of surface within forest canopy (Floyd et al, 1998). The parameters that are important in forest inventory are tree density, stand age and timber volume. These parameters are interrelated and also they depend on the tree growth and stand development. By visual interpretation, the different types of land cover classes are discriminated using the backscatter intensity and texture. The different types of forests can be discriminated from polarimetric SAR data and image fusion technique.

The changes in tone and texture are related to crown closure or foliage density. Backscatter is dependent on crown closure than height (Floyd et al, 1998). Backscatter is also sensitive to the target's electrical properties, including water content.




Fig 2.2: Penetration of different wavelengths in the canopyThe magnitude of the scattering mechanisms and the importance of the different components are dependent on geometric factors (e.g., structural attributes of trees, canopy and soil surface roughness) and dielectric properties of vegetation and underlying surface (e.g., moisture content of vegetation and soil) (Dobson et al., 1995). Wavelength, polarization and incidence angle of radiation control these scattering mechanisms (Leckie and Ranson, 1998) and the final backscatter as a result of surface and/or volume scattering.

In X band, which is a short wavelength band, the backscatter results mainly from the upper part of the canopy (Le Toan et al., 1992) and the leaves, twigs and small branches (Leckie and Ranson, 1998). There is little penetration of the radiation into the canopy; therefore, volumetric scattering and soil contribution to the final backscatter are weak. At C band, which is an intermediate wavelength, greater penetration of the radiation into the canopy enables further sources of scattering to be active and so there is some volume-scattering. The main sources of scattering at C band are secondary branches and leaves (Ranson and Sun, 1994; Leckie and Ranson, 1998). At longer L and P band wavelengths, the penetration of the radiation into the canopy is deeper and components from the lower parts of the canopy are included in the scattering (Le Toan et al., 1992), as well as the major woody biomass components (trunks and branches) (Dobson et al., 1992). Trunk-ground and crown-ground interactions are important at these wavelengths (Leckie and Ranson, 1998) and are mainly dependent on the canopy structure and openness. Foliage and mall branches act as attenuators of the radiation at these wavelengths (Kasischke et al., 1997). The main components and scattering mechanisms of the total backscatter from forests comprise backscatter from (1) crown surface and volume, (2) trunks, (3) direct from the ground, (4) crown-ground scattering and (5) double-bounce scattering from trunk and ground (Leckie and Ranson, 1998).

Direct backscatter from canopy top

Multiple scattering and volume scattering in the vegetation.

Direct backscatter from land surface.

The combination of multiple channels and polarizations provides greater advantage for estimating total biomass. This is due to SAR unique capabilities to distinguish woody from herbaceous biomass and to penetrate the vegetative canopy to detect underlying surface conditions (Harry Stern, 1998). Cross-polarization SAR gives accurate results in estimating aboveground biomass. Measurement of species diversity and biomass on both a spatial and temporal level may be possible through appropriately chosen remote sensing data types (Alex et al, 2003).

The intensity of radar backscatter is sensitive to the forest parameters such as diameter at breast height (dbh) and tree mean height. The saturation problem is also common in radar data. The saturation levels depend on the wavelengths (i.e. different Bands, such as C, L, P), polarization (such as HH, HV, VV and VH), and the characteristics of vegetation stand structure and ground conditions. The variation in the allocation of the biomass to various structures such as stems, branches, leaves; their sizes, numbers and orientation influence backscatter. Backscatter saturates at a biomass, which is related to Radar wavelength. C-band can measure forestry biomass up to app. 50 tons/ha, L-band can measure up to 100 tons/ha and P-band can measure up to 200 tons/ha (Floyd et al., 1998).

Biomass estimation from SAR data has been under investigation for the last two decades, the main conclusions being that the retrieval accuracy increases for increasing radar wavelength and the interferometric SAR (InSAR) coherence has the potential to provide stem volume estimates in some case comparable to in situ data.