CEE 610 / SCAS 660 1 Lab #8: Radar
SAR Processing and Analysis(Adapted from ENVI Radar tutorials)
Files used in this Lab
File Description
ndv_l.cdp L-band SIR-C subset in ENVI compressed data product (.cdp) format
pol_sig.roi Region of interest (ROI) file
ts0218_c.vvi C-Band VV
ts0218_c.cor C-Band correlation image
ts0218_c.dem C-Band DEM image
ts0218_c.inc C-Band incidence angle image
ts0218_l.dat L-Band Stokes matrix data
ts0218_p.dat P-Band Stokes matrix data
Background: SIR-C/SAR
SIR-C is a polarimetric SAR instrument that uses two microwave wavelengths: L-band (24
cm) and C-band (6 cm). The SIR-C radar system was flown as a science experiment on
the Space Shuttle Endeavor in April (SRL-1) and October 1994 (SRL-2), collecting high-
quality SAR data over many sites around the world. (A second radar system, XSAR, was
also flown on this mission, but these data are neither discussed nor processed here.)
Additional information about SIR-C is available on the NASA/JPL Imaging Radar Home
Page at http://southport.jpl.nasa.gov/.
Polarimetric SAR Processing
The data for this section are a subset of L-band Single Look Complex (SLC) SIR-C data that
cover the northern part of Death Valley, including Stovepipe Wells, a site of active sand
dunes and extensive alluvial fans at the base of mountains. These data were preprocessed
by reading and subsetting from tape and multilooking (averaging) to 13 m square pixels.
The data are provided in ENVI compressed data product (.cdp) format. This non-image
format is similar to the tape format and cannot be viewed until images are synthesized for
specific polarizations.
Synthesize Images
The SIR-C quad-polarization data provided with this tutorial and available are in a non-
image, compressed format. Images must be mathematically synthesized from the
compressed scattering matrix data. The advantage is that you can synthesize images with
any transmit and receive polarization combinations you want.
1. From the ENVI main menu bar, select Radar → Polarimetric Tools → Synthesize SIR-
C Data. An Input Product Data Files dialog appears.
2. Click Open File. A file selection dialog
appears.
3. Navigate to envidata\ndv_sirc and select
ndv_l.cdp. Click Open. When the filename
appears in the Selected Files L: field, click
OK. The Synthesize Parameters dialog
appears.
CEE 610 / SCAS 660 2 Lab #8: Radar
Default Polarization Combinations
Four standard transmit/receive polarization combinations—HH, VV, HV, and TP—are listed
in the Select Bands to Synthesize list of the Synthesize Parameters dialog. By default, all
of these bands are selected to be synthesized.
1. Enter ndv_l.syn in the Enter Output Filename field.
2. Click the Output Data Type drop-down list and select Byte. This scales the output data to
byte values. (If you will be performing quantitative analysis, the output should remain in
floating-point format.) Click OK. After processing is complete, four bands corresponding
to the four polarization combinations are added to the Available Bands List.
Other Polarization Combinations
It is possible specify the transmit and receive ellipticity and orientation angles when
synthesizing an image. We will not do that here.
Displaying and enhancing the images
The distribution of brightness values in radar imagery are frequently skewed. To see this,
examine the L-TP image (L-band, total polarization) image:
Gray Scale images
1. Display the L-TP band as a gray-scale image
2. From the image window, select Enhance →
Interactive Stretching. Note that the histogram
is skewed to the darker gray values and the
standard 2% linear stretch applied by ENVI is
not optimal for this type of distribution.
3. Enter 5 and 95 in the Stretch windows above the
histograms (or move the dotted vertical lines.)
4. From the histogram menu bar, select Stretch
Type → Gaussian. Click Apply. A Gaussian
stretch is applied with the specified low and high
cutoffs.
5. A square root stretch also tends to work well with this type of histogram distribution.
Compare linear and square-root stretches.
Color display
1. Select the RGB Color radio button in the Available Bands List. Select [L-HH], [L-VV],
and [L-HV] to display the bands as Red, Green and Blue respectively. The color
variations in the images are caused by variations in the radar reflectivity of the surfaces.
The bright areas in the sand dunes are caused by scattering of the radar waves by
vegetation (mesquite bushes). The alluvial fans show variations in surface texture due to
age and composition of the rock materials.
2. Adjust the stretch as desired (Gaussian and square-root stretches work well on all three
bands).
CEE 610 / SCAS 660 3 Lab #8: Radar
Define ROIs for Polarization Signatures
You can extract polarization signatures from a SIR-C compressed scattering matrix for a region
of interest (ROI) or a single pixel in a polarimetric radar image by selecting pixels or by drawing
lines or polygons within an image.
1. From the Display group menu bar, select Overlay → Region of Interest. An ROI Tool
dialog appears.
2. Four ROIs were previously defined and saved for use in extracting polarization signatures
for this tutorial. From the ROI Tool dialog menu bar, select File → Restore ROIs. A file
selection dialog appears.
3. Select pol_sig.roi. A dialog box appears, stating that the regions were restored. Click OK.
4. Regions named veg, fan, sand, and desert pvt appear in the table in the ROI Tool and are
drawn in the display group.
Extract Polarization Signatures
Polarization signatures are 3D representations of the complete radar scattering characteristics of
the surface for a pixel or average of pixels. They show the backscatter response at all
combinations of transmit and receive polarizations and are represented as either co-polarized or
cross-polarized. Co-polarized signatures have the same transmit and receive polarizations. Cross-
polarized signatures have orthogonal transmit and receive polarizations. Polarization signatures
are extracted from the compressed scattering matrix data using the ROIs for pixel locations.
Polarization signatures are displayed in viewer dialogs, as shown on the next page. To extract
polarization signatures, perform the following steps.
1. From the ENVI main menu bar, select Radar → Polarimetric Tools → Extract
Polarization Signatures → SIR-C. The filename ndv_l.cdp should appear in the Input
Data Product Files dialog. If not, click Open File and select this file. Click OK. The
Polsig Parameters dialog appears.
2. Select the four ROIs (veg, fan, sand, and desert pvt) by clicking Select All Items.
3. Select the Memory radio button and click OK. Four Polarization Signature Viewer
dialogs appear, one for each ROI. The polarization signatures are displayed as 3D wire
mesh surface plots and as 2D gray scale images. The X and Y axes represent ellipticity
and orientation angles, respectively. You can selectively plot the vertical axis as intensity,
normalized intensity, or dB by selecting Polsig_Data from the Polarization Signature
Viewer dialog menu bar.
4. Polarization signature statistics appear at the bottom of each Polarization Signature
Viewer dialog. Notice the range of intensity values for the different surfaces. The
smoother surfaces (sand and desert pvt) have low Z values. The rough surfaces (fan and
veg) have higher Z values. The minimum intensity indicates the pedestal height of the
polarization signature. The rougher surfaces have more multiple scattering and therefore
higher pedestal heights than the smoother surfaces. The shape of the signature also
indicates the scattering characteristics. Signatures with a peak in the middle show a
Bragg-type (resonance) scattering mechanism.
CEE 610 / SCAS 660 4 Lab #8: Radar
5. In any given Polarization Signature Viewer dialog, change the Z-axis by selecting
Polsig_Data → Normalized from the Polarization Signature Viewer dialog menu bar.
This normalizes the signature by dividing by its maximum; the signature is plotted
between 0 and 1. This representation shows the difference in pedestal heights and shapes
better, but it removes the absolute intensity differences.
6. Alternately, select Polsig_Data → Co-Pol and Cross-Pol to toggle between co-polarized
and cross-polarized signatures.
7. Use the left mouse button to drag a 2D cursor on the polarization signature image on the
right side of the plot. Note the corresponding 3D cursor in the polarization plot.
8. Click-and-drag any axis to rotate the polarization signature.
9. You can optionally output the signatures to a file or printer by selecting File → Save Plot
As or File → Print from the Polarization Signature Viewer dialog menu bar.
10. Close the Polarization Signature Viewer and ROI Tool dialogs when you are finished.
CEE 610 / SCAS 660 5 Lab #8: Radar
Adaptive Filters
Adaptive filters are used to reduce the speckle noise in a radar image while preserving the texture
information. Statistics are calculated for each kernel and used as input into the filter, allowing the
filter to adapt to different textures within the image.
1. From the ENVI main menu bar, select Radar (or Filter) → Adaptive Filters →
Gamma. A Gamma Filter Input File dialog appears with a list of open files. You can
apply a filter to an entire file or to an individual band.
2. In the Gamma Filter Input File dialog, click the Select by toggle button to choose Band.
3. Select [L-HH] under ndv_l.syn and click OK. The Gamma Filter Parameters dialog
appears.
4. Accept the default values, and select the Memory radio button. Click OK.
5. In the Available Bands List, click Display #1 and select New Display. Select the Gray
Scale radio button, select the new band name (Gamma), and click Load Band.
6. From the Display group menu bar, select Enhance → [Image] Square Root.
7. In the Available Bands List, click Display #2 and select Display #1. Select [L-HH]
under ndv_l.syn, and click Load Band.
8. From the Display #1 menu bar, select Enhance → [Image] Square Root.
9. From any Display group menu bar, select Tools → Link → Link Displays. The Link
Displays dialog appears. Click OK to link the gamma-filtered L-HH image (Display #2)
with the original L-HH image (Display #1).
10. Click in an Image window to toggle between the two images, using the dynamic overlay
feature. The figure below shows a portion of the original image (left) and the gamma-
filtered image (right).
11. Close Display #2 when you are finished. Leave Display #1 (ndv_l.syn) open for the next
exercise.
Slant-to-Ground Range Transformation
A radar system looks to the side and records the locations of objects using the distance from the
sensor to the object along the line of sight, rather than along the surface. An image collected
using this geometry is referred to as a slant range image. Slant range radar data have a systematic
geometric distortion in the range direction. The true, or ground range, pixel sizes vary across the
range direction because of the changing incident angles. This makes the image appear
compressed in the near range, relative to what it would look like if all of the pixels covered the
same area on the ground.
Slant-to-ground range correction for SIR-C is performed on synthesized images. In other words,
the correction is not performed on the entire SIR-C compressed data product file. However, this
file does store the required information in the CEOS header about the sensor orientation.
CEE 610 / SCAS 660 6 Lab #8: Radar
Preview CEOS Header
1. From the ENVI main menu bar, select Radar → Open/Prepare Radar File → View
Generic CEOS Header. A file selection dialog appears. You must select the original
unsynthesized data file from which to extract the necessary information.
2. Select ndv_l.cdp and click Open. A CEOS Header Report dialog appears. Scroll down
and note that the line spacing (azimuth direction) is 5.2 m, while the pixel spacing (slant
range direction) is 13.32 m. Close the CEOS Header Report dialog when you are finished
reviewing it.
3. Next, you will use the Slant-to-Ground-Range function to resample the image to square
13.32 m pixels, thus removing slant range geometric distortion.
Resample Image
1. From the ENVI main menu bar, select Radar → Slant to Ground Range → SIR-C. A
file selection dialog appears.
2. Select ndv_l.cdp and click Open. The Slant Range Correction Input File dialog appears.
3. Select ndv_l.syn and click OK. The Slant to Ground Range Correction Dialog appears.
ENVI automatically populates the Instrument height (km), Near range distance (km), and
Slant range pixel size (m) fields with information from the CEOS header. (Note the Near
Range Location. Does this match your interpretation of the look direction?)
4. Enter 13.32 in the Output pixel size (m) field to generate square ground-range pixels.
5. From the Resampling Method drop-down list, select Bilinear.
6. In the Enter Output Filename field, enter ndv_gr.img. Click OK. The input image is
resampled to square 13.32 m pixels. Four new bands appear in the Available Bands List.
Band 1 of the resampled image corresponds to the L-HH band of the original, slant-range
image (ndv_l.syn), Band 2 corresponds to L-VV, etc.
7. In the Available Bands List, click Display #1 and select New Display.
8. Select a band from the resampled image and click Load Band. The resampled image
appears in Display #2. Make sure Display #1 (ndv_l.syn) shows the corresponding
polarization band.
9. Compare the two images.
10. Close the displays.
CEE 610 / SCAS 660 7 Lab #8: Radar
TOPSAR Data and DEM Analysis
Background: TOPSAR Data
A full TOPSAR dataset from JPL includes polarimetric (quad-polarized) data for both P- and L-
bands and a C-band VV-polarization image. JPL generates a DEM from SAR interferometry
using the C-band antenna. Also provided are the correlation image and an incidence angle image
generated from the C-Band data.
This tutorial uses polarimetric synthetic aperture radar (SAR) data and a digital elevation model
(DEM) of Tarrawarra, Australia, generated from NASA Jet Propulsion Laboratory's (JPL's)
Topographic Synthetic Aperture Radar (TOPSAR) instrument, flown aboard a NASA DC-8
aircraft. The tutorial demonstrates input and display of the TOPSAR data and display and
analysis of the TOPSAR DEM using standard tools in ENVI. For the DEM, these include data
input; gray scale and color-density-sliced display; generation and overlay of elevation contours;
use of ENVI’s X, Y, and arbitrary profiles (transects) to generate terrain profiles; 3D perspective
viewing and image overlay; and generation of topographic modeling and feature images.
Display and Convert TOPSAR data
View TOPSAR Header
1. From the ENVI main menu bar, select
Radar > Open/Prepare Radar File > View AIRSAR/TOPSAR Header.
An AIRSAR/TOPSAR Input File selection dialog appears.
2. Navigate to Data\topsar and select ts0218_c.vvi. The AIRSAR File Information dialog appears,
listing information from the embedded AIRSAR Integrated Processor headers.
3. Close the AIRSAR File Information dialog
Load and Display Raw C-Band Image
1. From the ENVI main menu bar, select Radar > TOPSAR Tools > Open TOPSAR File.
A file selection dialog appears.
2. Select ts0218_c.vvi and click Open. This opens and displays the TOPSAR C-Band data
without converting to physical units (sigma zero), using the embedded TOPSAR header
to get the required file information. This also loads the image into the Available Bands
List. You could also open this file by selecting File > Open External File > Radar >
TOPSAR, or by selecting File > Open Image File, but you have to manually enter the file
parameters with the latter option.
3. In the Available Bands List, select the Gray Scale radio button, and click Load Band to
load the image.
4. Examine the geometry and characteristics of the image. (Double-click inside the Image
window to start the Cursor Location/Value tool.) This is a ground-range, C-Band, VV-
polarization image scaled to integer format. A scaling factor must be applied to the data to
convert to sigma zero (radar backscatter coefficient).
5. Observe the general magnitude of the pixel values.
CEE 610 / SCAS 660 8 Lab #8: Radar
Load and Display Raw DEM Image
1. From the ENVI main menu bar, select Radar > TOPSAR Tools > Open TOPSAR File.
A file selection dialog appears.
2. Select ts0218_c.dem and click Open. This opens the TOPSAR DEM data, using the
embedded AIRSAR/TOPSAR header to get the required file information. You could also
open this file by selecting File > Open Image File, but you have to manually enter the
file parameters.
3. In the Available Bands List, select a new display load the band. The DEM image appears
in a display group. Double-click inside the Display #2 Image window to start the Cursor
Location/Value tool. Observe the general magnitude of the integer pixel values, which
are in units of raw digital numbers (DNs), as stored in the DEM file.
5. From a Display group menu bar, select Tools > Link > Link Displays. The Link Displays
dialog appears. Click OK to link the two images. Click in an Image window to toggle
between the two images.
Convert Data Units
1. From the ENVI main menu bar, select Radar > TOPSAR Tools > Convert TOPSAR
Data. An Enter TOPSAR Filename dialog appears.
2. Select ts0218_c.vvi and click Open. A TOPSAR Conversion Parameters dialog appears.
ENVI automatically identifies all of the TOPSAR data based on the TOPSAR file-
naming convention. The VV Polarization, Correlation, Incidence Angle, and DEM
images are opened. The C-VV data are automatically converted to sigma zero, and DEM
data are converted to meters based upon values in the TOPSAR headers.
CEE 610 / SCAS 660 9 Lab #8: Radar
3. Click Spatial Subset and enter 1061 in the Line/To
field. This will match the size of the C-band data
and DEM to the P- and L-band data. Click OK.
4. In the Enter Output Filename field of the TOPSAR
Conversion Parameters dialog, enter topsar.img
and click OK. Four images are added to the
Available Bands List: VV Polarization, Correlation,
Incidence Angle, and DEM (m).
5. In the Available Bands List, click Display #2 and
select New Display
6. Load the C-VV sigma zero image by selecting the
VV Polarization band name and clicking Load
Band.
7. Double-click in the Display #3 Image window to
start the Cursor Location/Value dialog.
Observe the general magnitude of the pixel
values (sigma zero). 8. From a Display
group menu bar, select Tools > Link >
Link Displays. The Link Displays dialog
appears.
8. Click the Display #2 (DEM) toggle button
to select No. Click OK to link Display #1
and Display #3 (the two C-VV images).
Compare the raw and sigma zero images.
9. In the Available Bands List, click Display
#3 and select New Display.
10. Select DEM (m) and click Load Band.
11. Observe the general magnitude of the pixel values, which represent elevations in meters.
Note the large negative number (-2911.099854) associated with holes in the DEM and the
image border. These are not valid elevations and should be excluded from analysis using
ENVI’s masking functions. You will perform this step later.
12. From a Display group menu bar, select Tools > Link > Link Displays. Link the two
DEM images by toggling the display options in the Link Displays dialog as follows.
Click OK.
13. When you are finished comparing images, select Window > Close All Display Windows.
CEE 610 / SCAS 660 10 Lab #8: Radar
Synthesize P- and L-Band Data
Both the L-Band and P-Band data are distributed by JPL in compressed Stokes matrix format, which you
cannot directly view. ENVI provides utilities to decompress the data and synthesize them to image
format.
1. From the ENVI main menu bar, select Radar > Open/Prepare Radar File > Synthesize
AIRSAR Data. (This menu option also applies to TOPSAR data.) An Input Stokes Matrix Files
dialog appears.
2. Click Open File and select ts0218_l.dat. The L- and P-band Stokes matrix filenames appear in
the Input Stokes Matrix Files dialog.
3. Click OK. The Synthesize Parameters dialog appears. The “standard” polarization bands, L-HH,
L-VV, L-HV, L-TP (total power); P-HH, P-VV, P-HV, and P-TP (total power), are automatically
entered into the dialog. If you want additional polarizations, enter the Transmit and Receive
Ellipticity and Orientation angles into the appropriate text boxes in the upper-left part of the
dialog and click Add Combination.
4. Click the Output Data Type drop-down list and select Byte.
5. In the Enter Output Filename field, enter ts0218lp.syn. Click OK to synthesize the images.
6. In the Available Bands List, select one or more of the synthesized bands to display as a grayscale
or an RGB image.
7. Compare the L-Band and C-Band VV data using image linking and dynamic overlays.
8. Display a color image with
Red: L-HV (L ~ 20 cm)
Grn: L-TP
Blu: P-TP. (P ~ 50 cm)
9. Select Enhance > Interactive Stretching to display the image histograms. Move the view of the
image around and apply different enhancements to different areas (dark and bright).
10. When you are finished, close Displays.