ASF's SAR FAQ

SAR FAQ - Frequently Asked Questions

The Questions:

What does aperture mean?
So, what does synthetic aperture mean?
Why is radar often used in remote sensing?
(Why are radio waves, visible light, and infrared radiation the most common forms of electromagnetic radiation sensed by Earth observing satellites?)
How does radar "see" at night?
How does radar "see" through clouds?
How is radar data different from what I would see? Why isn't there any color?
What are some "rules of thumb" for SAR image interpretation?
What's the smallest object you can see in a SAR image?
What's the difference between resolution and pixel spacing?
How is this SAR data used?
What's the difference between slant range and ground range?
What does geocoded mean?
Why does it look like the mountains are "lying down"?
(What do foreshortening, layover, and radar shadowing mean?)
What does terrain correction mean?
What is a look (e.g. 4-look data)? What is speckle?
What do you mean by "Complex SAR Data"?
What is SAR interferometry?
What's the difference between ERS-1 and JERS-1 SAR data? Which should I use?
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How can I get ASF's data?
What area does ASF's data cover?
How long has ASF been downlinking SAR data?
(If you can't find the answer here, try: the Canada Center for Remote Sensing's Index of Remote Sensing Glossaries and Acronyms, ASF's Scientific SAR User's Guide, JPL's What is Imaging Radar, SIR-CED's Teacher Resource Guide, or ASF's SAR Processing documentation. If you still can't find the answers, try posting your question on JPL's radar imaging bulletin board.)

The Answers:
What does aperture mean?

Many people associate the word aperture with photography, where the term represents the diameter of the lens' opening. The camera's aperture then determines the area through which light is collected. Similarly, a radar antenna's length partially specifies the area through which it collects radar signals. The antenna's length is therefore also called its aperture.

Remember, light and radar just represent different wavelengths of electromagnetic radiation, so many terms and equations used in everyday optics also apply in radar theory.

So what does synthetic aperture mean?

In general the larger the antenna, the more unique information you can obtain about a particular viewed object. With more information, you can create a better image of that object (improved resolution). It's prohibitively expensive to place very large radar antennas in space, however, so researchers found another way to obtain fine resolution: they use the spacecraft's motion and advanced signal processing techniques to simulate a larger antenna.

A SAR antenna transmits radar pulses very rapidly. In fact, the SAR is generally able to transmit several hundred pulses while its parent spacecraft passes over a particular object. Many backscattered radar responses are therefore obtained for that object. After intensive signal processing, all of those responses can be manipulated such that the resulting image looks like the data were obtained from a big, stationary antenna. The synthetic aperture in this case, therefore, is the distance traveled by the spacecraft while the radar antenna collected information about the object. Please see the associated graphic.

The ERS-1 satellite's SAR sends out around 1700 pulses a second, collects about a thousand backscattered responses from a single object while passing overhead, and the resulting processed image has a resolution near 30 meters. The spacecraft travels around 4 kilometers while an object is "within sight" of the radar, implying that ERS-1's 10 meter x 1 meter radar antenna synthesizes a 4 kilometer-long stationary antenna!

Why is radar often used in remote sensing?
(Why are radio waves, visible light, and infrared radiation the most common forms of electromagnetic radiation sensed by Earth observing satellites?)

The wavelengths of electromagnetic radiation most commonly used for remotely sensing Earth are: the spectrum of visible light, a wide spectrum of radio wavelengths, and several infrared wavelengths. A partial explanation of why these wavelengths are preferable is outlined below. When radar (which employs radio waves) is selected from these possible choices, the decision is usually based upon radar's independence of solar illumination and weather conditions. See the questions: How does radar "see" at night? and How does radar "see" through clouds? for more details.

There is a good reason why our eyes sense the electromagnetic radiation (light) they do: visible light represents a significant portion of the electromagnetic radiation which can pass through Earth's atmosphere and ionosphere. A wide spectrum of radio waves, which radars employ, and some infrared radiation can also pass through to the Earth's surface.

There are many reasons why other wavelengths/frequencies of electromagnetic radiation don't make it through Earth's atmosphere. For example many people know that ozone in Earth's upper atmosphere helps protect us from ultraviolet radiation. This occurs because the structure of the ozone molecule is particularly sensitive to ultraviolet frequencies; it has a natural resonance near those frequencies. Think of a person swinging; he swings back and forth with a particular frequency. If you push him with the same frequency (every time he comes back) or at a related periodic frequency (say, every other time he comes back), he will keep going higher and higher. Incoming ultraviolet radiation likewise keeps "pushing" the ozone moleule at the structure's resonant frequency - in a sense like pushing the swinging person higher. Soon the ozone molecule breaks into an oxygen atom and an O2 molecule which go on to other adventures. The incoming ultraviolet radiation's energy was used to break apart the ozone molecule, a process by which we say the radiation was "absorbed." Many molecules in Earth's atmosphere have various kinds of resonances which absorb other frequencies of electromagnetic radiation. The visible spectrum, a wide spectrum of radio frequencies, and some infrared frequencies don't match well with those resonances, however, and thus are not much affected by absorption. These frequencies of electromagnetic radiation are therefore most commonly used for remote sensing purposes.

As a side note - some radar wavelengths reflect off the ionosphere and therefore cannot be used for remote sensing purposes. You may know a HAM radio operator who utilizes this phenomenon to talk to a companion halfway around the world. In this case radio waves are transmitted up to the ionosphere and reflected back down to Earth elsewhere, rather than passing through the ionosphere. This happens because the radio waves cause electrons in the ionosphere to oscillate, and the oscillating electrons in turn radiate electromagnetic waves.

How does radar "see" at night?

SAR instruments transmit radar signals and then measure how strongly those signals are scattered back. An analogy with photography can be made: when it's dark, a camera's flash sends out light and then the film records objects that the flash illuminates. In both cases the SAR and the camera are not dependent upon the sun because they provide their own illumination.

How does radar "see" through clouds?

Light does often make it through clouds, but that light has just been scattered all over the place, making it nearly impossible to tell how the light was oriented before it entered the cloud. This is why we can't see objects through clouds. The difference with radar is how much less it's distorted while passing through a cloud.

The reason why clouds scatter visible light while leaving radar undistorted is a matter of relative scale. Radar's longer wavelengths in effect average the properties of air with the properties and shapes of many individual water droplets, making the cloud look homogeneous - i.e. like moist air. Visible light has short enough wavelengths to respond to all the individual boundaries between air and water droplets. At each boundary the light is reflected to a new direction, and by the time it escapes the cloud, information on the light's original direction is hopelessly lost. The radar signals, on the other hand, are only affected while entering and exiting the cloud. Because they don't suffer multiple bounces, the radar waves are relatively undistorted by clouds.

How is radar data different from what I would see? Why isn't there any color?

(See the previous question for an explanation of why you don't see clouds in a typical radar image.)

Our eyes perceive what is called visible electromagnetic radiation, or electromagnetic radiation with wavelengths between 0.4 and 0.7 microns. Even though we can't see other wavelengths of electromagnetic radiation, they certainly affect us. Ultraviolet radiation, for example, can burn our skin or hurt our eyes, and X-Rays can inform us if we have broken a bone or have developed cavities in our teeth!

When we think about all the information light provides us about our world, and about how other electromagnetic waves impact our lives, it seems only natural that people would want to detect and "visualize" many other kinds of electromagnetic radiation. The Earth Observing System does just that; many satellites' instruments "see" certain electromagnetic waves and relay that data to a "brain" (computer), where the information is then converted into an image for humans to interpret. Each wavelength indicates something different about the imaged object, just as you might associate the wavelength corresponding to bright green light with young plants.

Visible light contains a range of wavelengths, but with radar we often measure one very specific wavelength. Just think of how differently things would look if you could only see yellow. Your eyes would only detect how brightly an object scattered yellow, so the reflection's intensity, not the color, is what would give you new and useful information. Similarly, radar antennas are often made to detect how brightly objects reflect one particular wavelength. Since there are no other "colors" (wavelengths) to mix in, we really only care about the backscatter's intensity and therefore often use greyscale in our visualizations of this data.

What are some "rules of thumb" for SAR image interpretation?

See the associated graphic regarding how radar signals interact with the Earth's surface. In general:
- Regions of calm water and other smooth surfaces appear black since the incident radar reflects away from the spacecraft.
- Surface variations near the size of the radar's wavelength cause strong backscattering. If the wavelength is a few centimeters long, dirt clods and leaves might backscatter brightly. A longer wavelength would be more likely to scatter off boulders than dirt clods, or tree trunks rather than leaves.
- A rough surface backscatters more brightly when it is wet.
- Wind-roughened water can backscatter brightly when the resulting waves are close in size to the incident radar's wavelength.
- Hills and other large-scale surface variations tend to appear bright on one side and dim on the other. (The side which appears bright was facing the SAR.) Mountains show this effect to the extreme, in part due to increased foreshortening. (See the section, Why does it look like the mountains are "lying down", for more details.)
- Due to the reflectivity and angular structure of buildings, bridges, and other human-made objects, these targets tend to behave as corner reflectors and show up as bright spots in a SAR image.
- A particularly strong response, say from a corner reflector or ASF's receiving antenna, can look like a bright cross in a processed SAR image. (The unusually strong sidelobes from the corner reflector's bright response impact brightness calculations for neighboring pixels.)
What's the smallest object you can see in a SAR image?

In ASF's full-resolution SAR images, you can distinguish objects as small as about 30 meters wide. Some of the smaller items that we've spotted have been ships and their wakes. When the SAR happens to be aligned at a certain angle, long thin objects such as roads or even the Alaskan oil pipeline can also be seen.

What's the difference between resolution and pixel spacing?

Pixel spacing represents how much area each pixel covers, while resolution indicates the smallest object you could pick out in an image. Each pixel represents one solid color, so of course you can't see anything within it. When you place other pixels around it, though, you might notice a few pixels are rather different in color than surrounding pixels and conclude that you have identified a distinct object. ASF's full-resolution ERS-1 SAR images have 12.5 m pixel spacing and about 30 m resolution. This means that each pixel represents a 12.5 x 12.5 m area on the ground, and you can discern individual objects which are around 30 m wide or larger.

How is this SAR data used?
SAR's ability to pass relatively unaffected through clouds, illuminate the Earth's surface with its own signals, and precisely measure distances makes it especially useful for the following applications:
- Sea ice monitoring
- Cartography
- Surface deformation detection
- Glacier monitoring
- Crop production forecasting
- Forest cover mapping
- Ocean wave spectra
- Urban planning
- Coastal surveillance (erosion)
- Monitoring disasters such as forest fires, floods, volcanic eruptions, and oil spills
Some of the larger current research projects include: mapping the Antarctic continent; mapping the Amazon rainforest; using interferometric analysis for predicting or analyzing earthquakes and volcanic activity; and generating "Arctic Snapshots" of the Arctic ice extent. Please view the ASF ERS-1 SAR Image Sampler or ASF's SAR Research Bibliography to learn about more applications of SAR data.

What's the difference between slant range and ground range?

The time it takes for a transmitted signal to travel to an object and back tells you how far away the object is. If you transmit a signal and receive two separate "echoes," you can use the time difference between when you record the first and second responses to determine the distance between the two sensed objects (dependent on where you stand). In this way the spaceborne SAR measures how far objects are from the spacecraft and the distance between the two objects, along the direction the spacecraft is looking. These distances are said to be recorded in slant range, since they are measured in a direction which is at an angle/slant to the ground.

Often researchers don't really care about distances from the spacecraft; they want to know about distances on the ground. Perhaps they need "real" (ground) distances to determine how much land was used for farming or what percentage of the sea was covered with ice, but the spacecraft samples the returning radar signals at specific time intervals which correspond to discrete distances from the spacecraft. That means that the data are originally in slant range. Given various parameters, the data can be processed such that each data value covers the same amount of area (distance) on the ground. We then say that the data are in ground range.

What does geocoded mean?

A standard ASF SAR image has gone through a lot of processing to look "normal." One step in this process involves manipulating the data such that each pixel represents a specific distance on the ground. The latitude and longitude coordinates of each image's center and corner pixels are also known. Sometimes, however, it's convenient to map the data onto a standard grid - such as a mercator projection. Then the pixels in each row would be evenly spaced in terms of longitude, and the entire row would be located at a specific latitude. The data would then be termed geocoded. It is often much easier to compare/overlay geocoded SAR data with non-SAR data sets.

Why does it look like the mountains are "lying down"?
(What do foreshortening, layover, and radar shadowing mean?)

The SAR very precisely measures distances between the spacecraft and objects on the ground. Sometimes, though, these measurements are quite different from what we're really interested in; we're used to working with ground distances - like how far we have to walk from one object to reach another. We can to some extent transform the SAR's information from satellite-object distances to object-object distances, by converting the data from slant to ground range. There are cases when this conversion is not very successful, however, such as when the SAR images a mountainous region.

When a spaceborne SAR looks down and to the side toward a steep mountain, many objects on the mountain's facing slope may appear to be located at the same distance from the spacecraft. (It's as though the farther out in range an object is, the higher/closer to the spacecraft the ground is raised by the mountain to compensate.) Since those many objects are located at nearly the same distance from the SAR, their backscattered signals will return to the spacecraft at about the same time. The SAR will conclude that the object located at that distance sure did backscatter brightly, mapping all those responses into one location while in truth (i.e. ground range) they came from many. This is called foreshortening, or layover in the extreme case where responses from, say, a mountain's peak are positioned before surrounding locations.

So far the SAR thinks it has seen a huge response from one location - the mountain slope facing the SAR. SAR illumination is much like solar illumination, in that it also has difficulty reaching the back side of a mountain. This phenomenon is called shadowing. After obtaining the very strong response, therefore, the SAR will suddenly find it quiet as few responses return from the mountain's opposing face. Note that the mountain's backfacing slope may be nearly parallel to the incoming radar, making it seem to the SAR that there are few responses for a significant distance. Next it will be time for responses from beyond the mountain to return, and life for the SAR will return to normal.

When viewing the resulting image, you will see that much of the mountain's (bright) facing slope was mapped onto a few pixels, while the (darker) backfacing slope was considered to cover many more pixels. Therefore it appears as though the mountains are lying over. Steeper topography or a smaller SAR look angle (meaning it looks more toward nadir and less to the side) can worsen foreshortening effects. (See this effect in the ERS-1, JERS-1 Comparison - White Mountains.) Generally the conversion from slant to ground range doesn't account for topography, so the apparent distortion is mapped into ground-range images as well.

If you have information about a region's topography, like a digital elevation model (DEM), you can make the slant to ground range conversion more sophisticated. In effect this terrain correction can compensate for foreshortening by spreading data representing the mountain's facing side into more pixels and compacting returns from the back face into fewer pixels. It's nearly impossible, though, to reliably extract the separate returns from data values representing the facing slope. Sometimes people try to compensate for shadowing as well. Knowing the mountain's slopes, they can approximate how the strength of backscattered signals were affected by the changed incidence angle and adjust results accordingly. These procedures, though inexact, can greatly improve SAR image analysis.

What does terrain correction mean?

If you have information about a region's topography, like a digital elevation model (DEM), you can make the slant to ground range conversion more sophisticated. In effect this terrain correction can compensate for foreshortening by spreading data representing the mountain's facing side into more pixels and compacting returns from the back face into fewer pixels. It's nearly impossible, though, to reliably extract the separate returns from data values representing the facing slope. Sometimes people try to compensate for shadowing as well. Knowing the mountain's slopes, they can approximate how the strength of backscattered signals were affected by the changed incidence angle and adjust results accordingly. These procedures, though inexact, can greatly improve SAR image analysis.

What is a look (e.g. 4-look data)? What is speckle?

As the spacecraft moves along in its orbit, the radar antenna transmits pulses very rapidly. It can therefore obtain many backscattered radar responses from a particular object while passing overhead. In fact the ERS-1 SAR records about 1,000 responses for a single object. The SAR processor could use all of these responses to obtain the object's radar cross-section (i.e. how brightly the object backscattered the incoming radar), but the result often contains quite a bit of speckle.

Speckle, generally considered to be noise, is due in part to the SAR's fine resolution and its signals' coherency. Speckle can be caused by an object that behaves as a very strong reflector at a particular alignment between itself and the spacecraft, or by a coherent sum of all the various responses within a grid cell which happen to randomly sum (as vectors with magnitude and phase) to a large resultant magnitude at a given phase.

To reduce speckle, the data are sometimes processed in sections which are later combined. With ERS-1's 1,000 samples per object, we might wish to use an object's first 250 responses to determine its radar cross-section. If we then processed the next 250 responses to get another estimate, and so on, we would end up with four estimates of the object's radar cross-section. Combining these four estimates, or looks, together would reduce the amount of speckle.

When an image has been processed as "4-looks": the first 250 (or so) samples of each viewed object were processed to make one image; the next 250 samples for each object were processed to make a second image; the third and fourth images were created with the next chunks of data; and the four images (looks) were combined to create the final result.

The more looks that are used to process an image, the less speckle there is. (The Complex-Format SAR Data Example demonstrates this.) It must be taken into account that information deemed important is also lost in this process, however, and that resolution is reduced. Several research groups are developing/improving algorithms to reduce speckle while saving as much accurate information as possible. (See the JPL Imaging Radar Homepage's Bulletin Board for the latest discussions on this topic.)

What do you mean by "Complex SAR Data"?

Used here the term "complex" refers to complex numbers, or complex-format data. You might be used to hearing of complex numbers with their "real" and "imaginary" components, also known as cosine and sine components. For example a wave might be described in complex format by: A*(cos(wt) + i*sin(wt)), where 'w' represents the wave's frequency and 'A' its amplitude. The cosine value would describe the wave's real component, sine the imaginary component, and the two would combine as vectors to provide the wave's overall phase (inverse tangent of sin/cos) and amplitude.

Both the cosine and sine components of backscattered SAR signals are measured and digitized on-board the satellite. The two resulting data streams are then transmitted to a ground station for further processing. People sometimes call these the 'I' (representing In-Phase, or the cosine or real component) and 'Q' (representing Quadrature, the 90 degrees shifted, sine or imaginary component) data streams. For standard processing these two data values are combined to obtain the composite signal intensity (sqrt[I^2 + Q^2]). Sometimes, though, it's desired to process the two data streams separately - usually to maintain the signals' phase information. Then ASF distributes the individually-processed I and Q data values for each pixel location, calling this product "Complex SAR Data." A more detailed example/tutorial of complex SAR data is also available. Complex SAR data are most often used for interferometric applications.

What is SAR interferometry?

SAR inteferometry makes use of the phase information contained in SAR data (described above). If you image an object from the same location at two different times and the backscattered signal's phase differs, you can infer that the object has moved. Similarly, the phase difference obtained when one object is imaged from two locations can be used to determine the object's height. For these reasons, SAR interferometry is often used to detect surface changes (e.g. for use in seismology) or to generate digital elevation maps. The following URL contains a good tutorial on SAR interferometry: SAR Interferometry and Surface Change Detection. ASF-STEP also provides some INSAR Resources. Some example interferograms can be found at the following locations:
What's the difference between ERS-1 and JERS-1 SAR data? Which should I use?
The primary differences between the ERS-1 and JERS-1 SAR instruments are:
- The ERS-1 SAR transmits C-band (5.66 cm) while JERS-1's SAR transmits L-band (23.5 cm) radar pulses.
- ERS-1's SAR has a 20.355 degree look angle compared to the JERS-1 SAR's 35.21 degree look angle.
Because a radar pulse reacts most strongly to surface variations near the size of its wavelength, the ERS-1 SAR signals backscatter significantly from small surface vegetation, dirt clods, or any such objects on the order of several centimeters. The JERS-1 SAR pulses, with their longer wavelengths, don't notice those small variations much. The JERS-1 signals instead: pass through the smaller vegetation to respond off the underlying geology; backscatter from tree trunks or larger branches rather than leaves; image larger (longer wavelength) ocean waves rather than small surface disturbances; etc.

As a result of the different look angles, the ERS-1 SAR data has more layover distortion while the JERS-1 SAR contains worse shadowing (described above).

For these reasons JERS-1 SAR images are generally preferred for geological studies, while the ERS-1 SAR data are often chosen for vegetation studies. These are general rules, but in truth many factors influence which images work best for a given application. Please see the ERS-1, JERS-1 Comparison for more information.

How can I get ASF's data?

Due to the proprietary nature of ASF's SAR data, you need to be an approved investigator to order the data. Don't worry, though! The application process is quite simple. Basically you just need to submit a short (about 2-page) proposal describing your research and why you would like to use the SAR data. NASA will also often grant data credits to research it deems to be in its interests. Please see ASF's New User Information for more details.

What area does ASF's data cover?

As a general rule, ASF downlinks real-time SAR data while a SAR-carrying satellite is within sight of ASF's antenna. For the ERS-1 and ERS-2 satellites, this means that most of ASF's data holdings cover regions within 3,000 km of Fairbanks, Alaska. Since JERS-1 orbits at a lower altitude, that data covers a slightly smaller region - within 2,700 km of Fairbanks.
There are exceptions! JERS-1 carries a tape recorder which can hold up to 10 minutes of SAR data. JERS-1 data has therefore occasionally been obtained elsewhere in the world and downlinked at ASF later. One notable example of this is the JERS-1 Amazon Mapping Project, for which ASF will process some 1,750 SAR scenes for each season. ASF is also expected to process all U.S.-requested RADARSAT data as well as ERS and RADARSAT data downlinked at the McMurdo, Antarctica station - data for the RADARSAT Antarctica Mapping Project for example. For various reasons ASF is also occasionally asked to process data obtained by other ground stations.
If you are looking for coverage of a particular region, your best bet might be to perform a search of ASF's data catalog. The EOSDIS V0-IMS data search and ordering system provides this capability, and you can begin a session by telnet to eosims.asf.alaska.edu port 12345. Help on using the system is also available.

How long has ASF been downlinking SAR data?

ASF began obtaining ERS-1 SAR data on September 7, 1991, and ASF's JERS-1 SAR data runs from May 1992 to the present. ERS-2 data collection began on October 1, 1995, and routine RADARSAT data collection at ASF began in June 1996.
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asfweb@www.asf.alaska.edu - March 19, 1996

SAR FAQ - Frequently Asked Questions

The Questions:

The Answers: