Available with Image Analyst license.
A Level 1 synthetic aperture radar (SAR) detected product must be processed before it can be used for visualization or analysis. Issues to address include updating orbit data, removing thermal noise, calibrating to retrieve a meaningful backscatter value, mitigating speckle, removing radiometric and geometric distortions, and rendering images with a large value range. The processing that must be performed is sensor and processing level specific.
The Synthetic Aperture Radar toolset, in the Image Analyst toolbox, contains eight tools you can use to generate calibrated, terrain-corrected, analysis-ready imagery data from supported SAR sensors.
| Tool | Description |
|---|---|
Downloads the updated orbit files for the input synthetic aperture radar (SAR) data. | |
Updates the orbital information in the synthetic aperture radar (SAR) dataset using a more accurate orbit state vector (OSV) file. | |
Corrects backscatter disturbances caused by thermal noise in the input synthetic aperture radar (SAR) data, resulting in a more seamless image. | |
|
Converts the input synthetic aperture radar (SAR) reflectivity into physical units of normalized backscatter by normalizing the reflectivity using a reference plane. | |
Corrects the input synthetic aperture radar (SAR) data for radiometric distortions due to topography. | |
Corrects the input synthetic aperture radar (SAR) data for speckle, which is a result of coherent illumination that resembles a grainy or salt and pepper effect. | |
Orthorectifies the input synthetic aperture radar (SAR) data using a range-Doppler backgeocoding algorithm. | |
Converts the scaling of the input synthetic aperture radar (SAR) data between amplitude and intensity and between linear and decibels (dB). |
Download and apply orbit state vectors
The accuracy of radiometric and geometric terrain corrections relies on the supplied orbit state vectors (OSVs). Most SAR sensors provide OSVs in their product metadata. Depending on the sensor, the OSVs may need to be updated to a more precise version, which is typically available within a few hours to a few weeks from the time of image acquisition.
For supported sensors, the Download Orbit File tool identifies and downloads the appropriate OSV file. The Apply Orbit Correction tool uses this downloaded OSV file to update the SAR product metadata.
Thermal noise removal
SAR images are distorted by additive thermal noise. Thermal noise is most apparent in images with low backscatter, such as in the cross-polarized channel (VH, HV), which is characterized by a narrower backscatter distribution.
Sensors that acquire data in Terrain Observations with Progressive Scans (TOPS) mode, such as Sentinel-1 and ICEYE, may exhibit varying thermal noise for individual subswath scans. This type of thermal noise commonly manifests as a sharp contrast between the subswath scans.
For supported sensors, the Remove Thermal Noise tool uses SAR product metadata to correct thermal noise.
Radiometric calibration
The Apply Radiometric Calibration tool uses the SAR product metadata to retrieve meaningful backscatter values. Radiometric calibration is the process of converting SAR products from image pixel digital numbers (DN) to the physical quantity of SAR backscatter intensity per unit area. The three calibration types are beta nought (
), sigma nought (
), and gamma nought (
). The unit area used for the calibration determines the calibration type.
Beta nought represents the radar reflectivity per unit area in slant range and is commonly known as radar brightness coefficient.
Sigma nought represents the radar reflectivity per unit area in ground range. Although sigma nought is a popular option for describing reflectivity, use it with caution. Sigma nought values vary with incidence angle, so a feature in the near range may have a different sigma nought value in the far range. If you're performing multitemporal analysis or change detection using sigma nought, use images from the same sensor and the same viewing geometry to ensure that changes in sigma nought are due to physical processes over time and not artifacts resulting from differences in viewing geometry.
Gamma nought represents the radar reflectivity per unit area in the plane perpendicular to the slant range. It is normalized using the incidence angle relative to the ellipsoid, so it provides a measurement value that is independent of range. If you want to use backscatter values to distinguish between unique features in a single image, use gamma nought instead of sigma nought. Also, use gamma nought if you are interested in multitemporal analysis or change detection using SAR imagery from different sensors or different viewing geometries (ascending versus descending). Gamma nought should only be used in these types of applications if the terrain is flat.
Radiometric terrain flattening
Due to the side-looking nature of SAR sensors, features facing the sensor appear artificially brighter than features facing away from the sensor. The Apply Radiometric Terrain Flattening tool corrects artificial radiometric values originating from complex topography and the sensor's viewing geometry.
Given an input digital elevation model (DEM) and an input SAR detected product calibrated to beta nought, the Apply Radiometric Terrain Flattening tool uses the range-Doppler approach to compute the illuminated area to produce a terrain-flattened gamma nought output. Alternatively, you can specify a terrain-flattened sigma nought output, which is normalized using the DEM-based local incidence angle.
An optional output is the simulated scattering area. This output can be used to gain insight on how terrain artificially impacts the calibrated data from terrain that has not been flattened.
Another optional output is a geometric distortion mask for identifying pixels affected by shadow, foreshortening, lengthening, or layover. The geometric distortion mask output allows you to mask terrain-flattened gamma nought or sigma nought output based on the geometric distortion type.
The last optional output is a geometric distortion raster containing a proxy for terrain slope, the look angle, the foreshortening ratio, and the local incidence angle. The geometric distortion output provides data that is used to perform the terrain flattening and to identify pixels impacted by geometric distortions.
Radiometric terrain flattening must be performed for applications interpreting a single image over any terrain, or for applications comparing multiple images from different sensors or the same sensor with different viewing geometries over any terrain.
Despeckle
SAR images are characterized by noise-like anomalies known as speckle. This inherent condition results from the constructive and destructive interference of the backscattered signal. The Despeckle tool provides several speckle filters to improve the signal-to-noise ratio of the SAR image. The speckle filters available are Lee, Enhanced Lee, Refined Lee, Frost, Kuan, and Gamma MAP. These filters use local pixel statistics to optimize the speckle suppression while conserving feature detail. To preserve the statistical properties needed for these filters, it is recommended that you use the Despeckle tool before geometric terrain correction, which resamples and reprojects the data.
Geometric terrain correction
Since SAR sensors are side looking, features facing the sensor appear compressed, while features facing away from the sensor appear stretched. The Apply Geometric Terrain Correction tool corrects geometric distortions, shifting the pixels to their correct geolocation.
The Apply Geometric Terrain Correctiontool uses the range-Doppler approach and the input DEM to orthorectify the input SAR image. A DEM with a resolution close to, or higher than, the input SAR data is recommended for most applications. For applications in which no terrain is present, you can omit the input DEM. The Apply Geometric Terrain Correction tool can use the range-Doppler approach and the geolocation grid from the product metadata to orthorectify the input SAR image.
Conversion to decibels
The final step to prepare analysis-ready data is to convert the unitless (linear) backscatter intensity to decibels (dB). The Convert SAR Units tool converts the linear backscatter intensity to decibels using a simple logarithmic conversion. The logarithmic conversion reduces the range of backscatter intensity values to improve image visualization and interpretation.