Process Sentinel-1 SAR data

A Sentinel-1 Level 1 synthetic aperture radar (SAR) image must be processed before it can be used for visualization or analysis. The aim of processing is to improve the satellite imagery by removing unwanted noise and distortions and enhancing some image features. In this tutorial, as an environmentalist working on a Galveston Bay Protection Project in Texas, you want to use SAR imagery to examine various trends and activities in the bay and the nearby suburbs. You'll process Sentinel-1 Ground Range Detected (GRD) data in ArcGIS Pro to generate analysis-ready SAR imagery.

Issues that must be addressed when preparing SAR imagery include updating orbit data, removing thermal noise, calibrating to retrieve a meaningful backscatter value, mitigating speckle, removing radiometric and geometric distortions, and converting the image scaling to a different unit. The Synthetic Aperture Radar toolset in the Image Analyst toolbox allows you to perform all these improvements. You can learn more about SAR processing and see an overview of the Sentinel-1 GRD workflow in the documentation.

If you're not yet familiar with SAR imagery, try the Explore SAR satellite imagery tutorial first.

This tutorial was last tested on May 18, 2023, using ArcGIS Pro 3.1. If you're using a different version of ArcGIS Pro, you may encounter different functionality.

Requirements

• ArcGIS Pro (see options for software access)
• ArcGIS Image Analyst

Download orbit file and apply orbit correction

First, you'll download and open the project in ArcGIS Pro. Then, you'll start the preparatory processing of the SAR imagery by updating its orbital information.

Download and open the project

You'll download a project that contains all the data for this tutorial and open it in ArcGIS Pro.

1. Download the Process_Sentinel_1_SAR_Data.zip file and locate the downloaded file on your computer.

   Note:

   Most web browsers download files to your computer's Downloads folder by default.

2. Right-click the Process_Sentinel_1_SAR_Data.zip file and unzip it to a location on your computer, such as drive C.

   Tip:

   As you unzip the file, if you get an error message about the file names being too long, try unzipping it in a folder with the shortest possible path, such as C:\Projects\.

3. Open the extracted Process_Sentinel_1_SAR_Data folder and double-click Process_Sentinel_1_SAR_Data.aprx to open the project in ArcGIS Pro.

   

4. If prompted, sign in to your ArcGIS organizational account or into ArcGIS Enterprise using a named user account.

   Note:

   If you don't have access to ArcGIS Pro or an ArcGIS organizational account, see options for software access.

   The project opens.

   

   Currently, the map contains only the default topographic basemap, centered on the Galveston Bay in Texas. The SAR image you'll process throughout this tutorial is included in the project; you'll add it to the map.

5. On the ribbon, click the View tab. In the Windows group, click Catalog Pane.

   

   The Catalog Pane appears.

6. In the Catalog pane, click the arrow next to Folders to expand it. Similarly, expand Process_Sentinel_1_SAR_Data and Data.

   

   The Data folder contains all the data you'll use in this tutorial. The SAR image is contained in the S1B_S6_GRDH_1SDH_20170823T002549_20170823T002612_007060_00C6FB_C69E.SAFE folder.

   Note:

   This image is a Ground Range Detected (GRD) SAR data product from the European Space Agency Copernicus Sentinel-1 mission and it was retrieved from the Copernicus Open Access Hub. You can learn more about SAR GRD and other SAR products commonly used to deliver SAR imagery in SAR Satellite Data. The product folder's long name corresponds to the granule name for the scene. You can learn more about the naming conventions and product folder file structure in Level-1 Product Formatting in the ESA Sentinel help.

7. Expand the S1B_S6_GRDH_1SDH_20170823T002549_20170823T002612_007060_00C6FB_C69E.SAFE folder, right-click manifest.safe, and choose Add To Current Map.

   

   Before the image appears on the map, a window prompts you to build pyramids and calculate statistics.

   Pyramids are reduced-resolution overviews of the data at different scales, which are used to improve the drawing speed. Statistics are required to perform certain tasks on the imagery, such as rendering it with a stretch.

   Note:

   Learn more about building pyramids and calculating statistics.

8. In the Build Pyramids and Calculate Statistics window, for Pyramids, confirm that the Build option is checked. For Statistics, confirm that the Calculate option is checked.

   

   Tip:

   Based on your ArcGIS Pro settings, one or both of these options may be running by default and will not be listed. You can change these settings by clicking Project on the ribbon, and then choosing Options, Raster and Imagery, and Raster Dataset.

9. Click OK.

   After a few moments, the image appears on the map.

   

   You'll give the layer a more meaningful name.

10. In the Contents pane, click the S6_manifest layer once to select it, and click it again to switch to edit mode. Type Galveston_Bay_S1_GRD and press Enter.

    

    Tip:

    To view more information about the SAR image, right-click Galveston_Bay_S1_GRD, choose Properties, and click the Source tab.

Download the orbit file

When preparing a SAR image for analysis, an important step is to apply orbit correction. No matter how fine-tuned a satellite's orbit may be, the location of the satellite will drift. This could be due to atmospheric drag and solar winds, the Earth's imperfect sphere attributed to a non-uniform gravitational field, or other massive objects in the solar system that perturb the satellite's orbit with their gravity. Because of this drift, periodic adjustments are needed to keep the satellite on the right track. Thus, it is imperative to have the most up-to-date orbital files to get the precise location of the satellite at the time the image was captured.

You'll download the updated orbit state vector (.osv) file, which contains precise orbital information such as velocity and position of the Sentinel-1 satellite. You'll do that by using the Download Orbit File tool from the Image Analyst toolbox. Reading the image metadata, the tool identifies the appropriate Sentinel-1 .osv file and downloads it to the local image folder.

1. On the ribbon, click the View tab. In the Windows group, click the Geoprocessing button.

   

   The Geoprocessing pane appears.

2. In the Geoprocessing pane, click the Toolboxes tab.

   

3. Expand Image Analyst Tools and the Synthetic Aperture Radar toolset.

   

   This toolset contains the SAR geoprocessing tools that you'll use throughout the tutorial.

4. Click the Download Orbit File tool to open it.

   

5. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD.
   • For Orbit Type, confirm that Sentinel Precise is selected.
   • Under Login Credentials, ensure that Username and Password are left blank.

   

6. Click Run.

   The orbit file is downloaded to the location of the input SAR image.

   Tip:

   Two OSV options are available for the Orbit Type parameter: Sentinel Precise and Sentinel Restituted. Restituted .osv files are available through the European Space Agency (ESA) within three hours of image acquisition. Precise .osv files are available through ESA within three weeks of image acquisition. If available, it is preferable to use Sentinel Precise, which is 20 times more accurate than Sentinel Restituted. You can learn more about these options in Precise Orbital Products and Requirements. Sentinel-1 .osv files are downloaded from the Copernicus Sentinels POD Data Hub.

Apply orbit correction

Next, you'll update the orbital information in the SAR image with the .osv file using the Apply Orbit Correction tool.

1. In the Geoprocessing pane, click the Back button.

   

2. Under Synthetic Aperture Radar, click the Apply Orbit Correction tool.

   

3. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD.
   • Confirm that the Input Orbit File parameter is populated with the orbit file you downloaded.

   

   Tip:

   Optionally, you can browse to the orbit file on your drive by clicking the Browse button next to the Input Orbit File parameter.

   

   Browse to Project, Folders, Data, and S1B_S6_GRDH_1SDH_20170823T002549_20170823T002612_007060_00C6FB_C69E.SAFE. The orbit file is named S1B_OPER_AUX_POEORB_OPOD_20210309T091152_V20170821T225942_20170823T005942.EOF.

4. Click Run.

   After the tool has run, the message Apply Orbit Correction completed appears. No new layer is created, but the original image is updated. Although the changes may not be visible to the human eye, this step is important for the accuracy of later processing and analyses.

   Note:

   The color of the image rendering may look slightly altered, but that has no impact on the pixel values or the rest of the workflow.

   Tip:

   Optionally, you can see the changes that occurred on the drive. Open a Microsoft File Explorer window and browse to the S1B_S6_GRDH_1SDH_20170823T002549_20170823T002612_007060_00C6FB_C69E.SAFE folder. You'll see a newly created manifest.safe.aux.xml file. This file can be opened with any text editor and will show that the metadata has been updated with the new orbit state vector information.

   

5. On the Quick Access Toolbar, click Save Project.

   

In the first part of the workflow, you downloaded and opened an ArcGIS Pro project. You then downloaded an .osv file containing precise orbit information and used it to apply an orbit correction to the SAR image.

Complete SAR processing

Next, you'll apply several tools to the SAR image to transform it into an analysis-ready layer. These tools will remove the thermal noise, apply radiometric calibration, apply radiometric terrain flattening, despeckle the image, apply geometric terrain correction, and convert the SAR unit.

Remove thermal noise

First, you'll correct backscatter disturbances caused by thermal noise in the input SAR data to obtain a more seamless image. You'll do that with the Remove Thermal Noise tool. Thermal noise, or instrument noise, is caused by microscopic motions of electrons due to temperature mostly from the internal circuitry of the satellite. Thermal noise is most apparent in areas of low backscatter such as permanent water bodies like the ocean and in cross-polarized scenes.

1. In the Geoprocessing pane, click the Back button.
2. Click the Remove Thermal Noise tool.

   

3. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD.
   • Confirm that Output Radar Data is automatically populated.
   • For Polarization Bands, check the HH and HV boxes.

   

   The Sentinel-1 satellite transmits signals in two polarizations, in this case HH and HV, which are stored as two separate raster bands in the SAR image. You will remove the thermal noise from both polarization bands.

4. Click Run.

   After a few moments, the new Galveston_Bay_S1_GRD_TNR.crf raster layer appears.

   

   You'll examine the difference between the two SAR layers. First, you'll apply a similar symbology to both layers.

5. In the Contents pane, verify that the Galveston_Bay_S1_GRD_TNR.crf layer is selected.

   

6. On the ribbon, click the Raster Layer tab. In the Rendering group, click the Symbology button.

   

   The Symbology pane for the Galveston_Bay_S1_GRD_TNR.crf layer appears.

7. In the Symbology pane, set the following parameters:
   • For Primary symbology, choose Stretch.
   • For Band, choose the HV polarization.
   • For Gamma, type 2.0.

   

   This rendering shows only the HV polarization band, which will enable a clear comparison between layers for the purpose of this tutorial. The gamma (degree of contrast) is also increased to brighten the image. On the map, the Galveston_Bay_S1_GRD_TNR.crf layer updates to its new display.

   

   Next, you'll symbolize the other layer.

8. In the Contents pane, uncheck the box next to the Galveston_Bay_S1_GRD_TNR.crf layer to turn it off. Click the Galveston_Bay_S1_GRD.crf layer to select it.

   

   You can now see the Galveston_Bay_S1_GRD.crf layer on the map, and its current symbology settings display in the Symbology pane.

9. In the Symbology pane, set the following parameters:
   • For Primary symbology, choose Stretch.
   • For Band, choose the HV polarization.
   • For Number of standard deviations, type 2.
   • For Gamma, type 2.0.

   

   On the map, the layer updates to its new display. You'll compare the two images, looking at an example of a location where thermal noise removal is evident.

10. On the ribbon, on the Map tab, in the Navigate group, click Bookmarks and choose Bookmark 1.

    

    The map updates to the position specified by the bookmark, showing the Galveston Bay on the north side and the Gulf of Mexico on the south side.

11. In the Contents pane, check the box next to the Galveston_Bay_S1_GRD_TNR.crf layer to turn it back on. Click the layer to select it.

    

12. On the ribbon, click the Raster Layer tab. In the Compare group, click the Swipebutton.

    

13. On the map, drag the swipe handle repeatedly from side to side to peel off the top layer and reveal the layer underneath.

    

    The thermal noise has been reduced over the water bodies (represented in black and darker tones).

14. When you are done examining the images, in the Contents pane, right-click Galveston_Bay_S1_GRD_TNR.crf and choose Zoom To Layer.

    

Apply radiometric calibration

Next, you'll use the Apply Radiometric Calibration tool. Calibrating SAR data is necessary to obtain meaningful backscatter that can be related to the physical properties of features in the image.

1. At the bottom of the Symbology pane, click the Geoprocessing tab to return to the Geoprocessing pane.

   

2. In the Geoprocessing pane, click the Back button.
3. Click the Apply Radiometric Calibration tool to open it.

   

4. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD_TNR.crf.
   • Confirm that Output Radar Data is automatically populated.
   • For Polarization Bands, check the HH and HV boxes.
   • For Calibration Type, confirm that Beta nought is selected.

   You are using the default Beta nought calibration, which will be required when you later perform radiometric terrain flattening.

   Note:

   Learn more about the calibration options in the Apply Radiometric Calibration tool documentation.

   

5. Click Run.

   After a few moments, the new Galveston_Bay_S1_GRD_TNR_CalB0.crf raster layer appears. You'll render this layer with a stretch.

6. In the Contents pane, under Galveston_Bay_S1_GRD_TNR1_CalB0.crf, click one of the layer's symbols to open the Symbology pane.

   

   Tip:

   This is another way of opening the Symbology pane.

7. In the Symbology pane, set the following parameters:
   • For Primary symbology, choose Stretch.
   • For Band, choose the HV polarization.
   • For Gamma, type 2.0.

   You'll compare the last two images with the Swipe tool.

8. In the Contents pane, click the Galveston_Bay_S1_GRD_TNR_CalB0.crf layer to select it.
9. If necessary, on the ribbon, on the Raster Layer tab, in the Compare group, click the Swipe button.

   Note:

   The swipe functionality should have remained turned on since you last used it. If so, you don't need to click the Swipe button again.

10. On the map, drag the swipe handle repeatedly from side to side to peel off the top layer and reveal the layer underneath.

    

    There is no visual difference in the imagery.

11. In the Contents pane, compare the values for Galveston_Bay_S1_GRD_TNR_CalB0.crf and Galveston_Bay_S1_GRD_TNR.crf.

    

    The radiometric calibration process transformed the value range dramatically because it normalized the backscatter values. However, that didn't change the relative values between the pixels of the image, which is why the Swipe tool didn't reveal any difference with the precalibration image.

Apply radiometric terrain flattening

Next, you'll correct the input SAR data for radiometric distortions due to topography using the Apply Radiometric Terrain Flattening tool. Due to the side-looking nature of SAR sensors, ground features facing the sensor appear artificially brighter and features facing away from the sensor appear artificially darker. Radiometric terrain flattening normalizes the backscatter values to eliminate these distortions.

To perform radiometric terrain flattening, you'll need a DEM layer, which provides elevation data about the extent covered by the SAR image. The project you downloaded contains a DEM layer that you'll add to the map.

1. At the bottom of the Symbology pane, click the Catalog tab to return to the Catalog pane.

   

2. In the Catalog pane, expand Folders, Process_Sentinel_1_SAR_Data, and Data.
3. Right-click Texas_DEM_90m.tif and choose Add To Current Map.

   

   The DEM layer appears on the map.

4. In the Contents pane, under Texas_DEM_90m.tif, click the symbol.

   

5. In the Symbology pane, for Color scheme, click the drop-down arrow and check the box next to Show names. Choose the Elevation #10 color scheme.

   

   On the map, the layer updates with the new symbology.

   

   Note:

   A DEM is a representation of the bare ground topographic surface of the Earth excluding trees, buildings, and any other surface objects. The Texas_DEM_90m.tif layer is a Copernicus Global DEM with 90 meter resolution. Each pixel represents the elevation above the sea level (in meters) at this location.

   Currently, the DEM layer hides the SAR imagery layers.

6. In the Contents pane, drag the Texas_DEM_90m.tif layer under all the SAR layers.

   

   The map updates to show the top SAR image above the DEM.

   

   Next, you'll run the Apply Radiometric Terrain Flattening tool.

7. At the bottom of the Symbology pane, click the Geoprocessing tab. In the Geoprocessing pane, click the Back button.
8. Click the Apply Radiometric Terrain Flattening tool to open it.

   

9. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD_TNR_CalB0.crf.
   • Confirm that Output Radar Data is automatically populated.
   • For DEM Raster, choose Texas_DEM_90m.tif.
   • Confirm that the Apply geoid correction box is checked.
   • For Polarization Bands, check the HH and HV boxes.
   • For Calibration Type, verify that Gamma nought is selected.

   Note:

   This DEM layer has a resolution of 90 meters per pixel, which is sufficient for this workflow. For further accuracy gains, you can use higher resolution DEM data.

   

10. Click Run.

    The tool might take a few minutes to process. When the process is complete, the new Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0.crf raster layer appears on the map. You'll render this layer similarly to the previous ones.

11. In the Contents pane, under Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0.crf, click one of the layer's symbols to open the Symbology pane.

    

12. In the Symbology pane, set the following parameters:
    • For Primary symbology, choose Stretch.
    • For Band, choose the HV polarization.
    • For Gamma, type 2.0.

    You'll compare this image with the previous one, looking at an example of a location where radiometric terrain flattening is evident.

13. On the ribbon, on the Map tab, click Bookmarks and choose Bookmark 2.

    

    The map updates to the position specified by the bookmark, showing the McCarty Road Landfill hill and its surroundings.

14. In the Contents pane, select the Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0.crf layer.

    

15. If necessary, on the ribbon, on the Raster Layer tab, click the Swipe button.
16. On the map, drag the swipe handle repeatedly from side to side to peel off the top layer and reveal the layer underneath.

    

    The McCarty Road Landfill hill at the center of the extent has areas where the brightness has changed. This is because the radiometry values were adjusted in the regions affected by foreshortening and layover.

    Note:

    Learn about the various distortion types in the Fundamentals of Synthetic Aperture Radar (SAR) guide.

17. When you are done examining the images, in the Contents pane, right-click Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0.crf and choose Zoom To Layer.

Despeckle the imagery

Next, you'll correct the input SAR data for speckle by using the Despeckle tool. Speckle refers to the grainy or salt and pepper effect that can be seen throughout the SAR image. The backscatter recorded for a single pixel is the result of the radar wave interacting with multiple features or objects within that pixel of the ground scene. When those interactions interfere constructively, they form a bright pixel. When they interfere destructively, they form a dark pixel. Shades of gray correspond to interference that's neither fully constructive nor destructive.

1. At the bottom of the Symbology pane, click the Geoprocessing tab. In the Geoprocessing pane, click the Back button.
2. Click the Despeckle tool to open it.

   

3. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0.crf.
   • Confirm that Output Radar Data is automatically populated.
   • For Polarization Bands, check the HH and HV boxes.

   

4. Click Run.

   After a few moments, the new Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk.crf raster layer appears on the map. You'll render this layer similarly to the previous ones.

5. In the Contents pane, under Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk.crf, click one of the layer's symbols to open the Symbology pane.

   

6. In the Symbology pane, set the following parameters:
   • For Primary symbology, choose Stretch.
   • For Stretch type, choose Standard Deviation.
   • For Band, choose the HV polarization.
   • For Gamma, type 2.0.

   You'll compare this image with the previous one, looking at an example of a location where despeckling is evident.

7. On the ribbon, on the Map tab, click Bookmarks and choose Bookmark 3.

   

   The map updates to the position specified by the bookmark, within the Trinity River National Wildlife Refuge.

8. In the Contents pane, select the Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk.crf layer.

   

9. If necessary, on the ribbon, on the Raster Layer tab, click the Swipe button.
10. On the map, drag the swipe handle repeatedly from side to side to peel off the top layer and reveal the layer underneath.

    

    The grain, or speckle, has been filtered out over the Trinity River National Wildlife Refuge land.

11. When you are done examining the images, in the Contents pane, right-click Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk.crf and choose Zoom To Layer.

Apply geometric terrain correction

Earlier in the workflow, you used the DEM layer to correct radiometric distortions. You'll use the DEM layer again, this time to correct for geometric distortions and orthorectify the input SAR data. Orthorectification is the process of correcting apparent changes in the position of ground objects caused by the perspective of the sensor view angle and ground terrain. You'll perform orthorectification with the Apply Geometric Terrain Correction tool.

1. At the bottom of the Symbology pane, click the Geoprocessing tab. In the Geoprocessing pane, click the Back button.
2. Click the Apply Geometric Terrain Correction tool to open it.

   

3. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_ Dspk.crf.
   • Confirm that Output Radar Data is automatically populated.
   • For Polarization Bands, check the HH and HV boxes.
   • For DEM Raster, select Texas_DEM_90m.tif.

   Tip:

   You should use a DEM whenever land features are included in the radar scene. If no DEM is specified or in areas that are not covered by a specified DEM, an approximated DEM, interpolated from metadata tie points, will be created. You should use the tie-point approach for full ocean radar scenes only.

   

4. Click Run.

   After a few moments, the new Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC.crf raster layer appears on the map. You'll render this layer similarly to the previous ones.

5. In the Contents pane, under Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC.crf, click one of the layer's symbols to open the Symbology pane.
6. In the Symbology pane, set the following parameters:
   • For Primary symbology, choose Stretch.
   • For Stretch type, choose Standard Deviation.
   • For Band, choose the HV polarization.
   • For Gamma, type 2.0.

   You'll compare this image with the previous one, looking at an example of location where geometric terrain correction is evident.

7. On the ribbon, on the Map tab, click Bookmarks and choose Bookmark 4.

   

   The map updates to the position specified by the bookmark, showing the Union Pacific railroad bridge. To get a clear reference point, you'll change the basemap.

8. On the ribbon, click the Map tab. In the Layer group, click Basemap and choose Imagery Hybrid.

   

   The map updates. The new basemap includes a hybrid reference layer, which shows important features and labels. The Union Pacific railroad bridge is shown crossing the lake diagonally.

   

9. In the Contents pane, select the Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC.crf layer.

   

10. If necessary, on the ribbon, on the Raster Layer tab, click the Swipe button.
11. On the map, drag the swipe handle repeatedly from side to side to peel off the top layer and reveal the layer underneath.

    

    The Union Pacific railroad bridge in the imagery is now more precisely geolocated and aligned to the hybrid reference layer. Furthermore, on the western shore next to Michael Moncrief Park, the distortion has been corrected.

12. When you are finished examining the images, in the Contents pane, right-click Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC.crf and choose Zoom To Layer.

    The SAR image displays over the Imagery basemap with the hybrid reference layer displaying on top.

    

13. On the ribbon, on the Map tab, in the Navigate group, click the Explore button to exit the swipe mode.

    

Convert SAR units

Next, you'll convert the scaling of the SAR data between linear and decibels (dB) using the Convert SAR Units tool. Because the dB is a logarithmic unit, it is a convenient way of manipulating and visualizing large numbers and large dynamic ranges. Thus, converting the units to dB will simplify the SAR image interpretation and improve its display, as it will reduce the range of amplitude or intensity values. After the conversion, the positive values will represent backscatter toward the sensor and negative values will represent backscatter away from the sensor.

You don't need the DEM layer any longer, so you'll turn it off.

1. In the Contents pane, check the box next to the Texas_DEM_90m.tif layer to turn it off.

   

2. At the bottom of the Symbology pane, click the Geoprocessing tab. In the Geoprocessing pane, click the Back button.
3. Click the Convert SAR Units tool to open it.

   

4. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC.crf.
   • Confirm that Output Radar Data is automatically populated.
   • For Conversion Type, confirm that Linear to dB is selected.

   

5. Click Run.

   After a few moments, the new Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC_dB.crf raster layer appears on the map.

   

   You have now performed the entire preparatory processing workflow and the SAR image is ready for visualization and analysis. You can view the history of these preparatory steps in the image properties.

6. In the Contents pane, right-click Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC_dB.crf and choose Properties.

   

7. In the Layer Properties window, click Source. Expand Processing History.

   

8. Optionally, expand some of the Processing History items to view more details.
9. Press Ctrl+S to save the project.

You've completed the processing of the SAR image.

Explore analysis-ready SAR imagery

Now that the SAR image has been processed, you'll visualize it as a color composite and interpret some of the features it contains.

Create a color composite

You'll create a color composite image using the Create Color Composite tool. As you saw earlier, the SAR image is composed of two polarization bands: HH and HV. While you can view each band independently, combining them will create a richer view of the landscape and will allow you to distinguish more clearly surface characteristics such as water, land, and urban structures. You can do that by creating a color composite, in which each band will be assigned to the red, green, or blue (RGB) display channels. Creating a color composite will result in an image where ground features can be identified based on color.

1. In the Geoprocessing pane, click the Back button.
2. Click the Create Color Composite tool to open it.

   

3. Set the following tool parameters:
   • For Input Radar Data, choose Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC_dB.crf.
   • Confirm that Output Radar Data is automatically populated.
   • For Method, choose Band names.
   • For Red Expression, type HH.
   • For Green Expression, type HV.
   • For Blue Expression, type HH-HV.

   

   Because the original image has two bands (HH and HV), there is not a third band available to assign to the Blue Expression parameter. Instead, you populate it with the math formula HH-HV. This means that for each pixel in the image, the value for the HV band will be subtracted from the value in the HH band. The result will act as a third band that will be displayed through the blue channel and will further highlight interesting features of the landscape.

   Note:

   The band math used depends on the units of the input SAR data. If the input SAR data is in decibels, the band combination must be HH for red, HV for green, and HH-HV for blue. If the input SAR data is in linear units, use HH for red, HV for green, and HH/HV for blue.

4. Click Run.

   The new Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC_RGB.crf raster layer appears on the map.

   

   The color composite shows water bodies in blue and vegetated areas in light green. Urban structures and other types of human-made structures appear in yellow, white, or pink. You can also see some residual noise in dark green tones along the edges of the scene.

5. Press Ctrl+S to save the project.

Interpret SAR imagery

Next, you'll explore the remaining bookmarks to visualize how the image composite represents different types of features. First, you'll turn off the layers you don't need.

1. In the Contents pane, turn off all the layers except Galveston_Bay_S1_GRD_TNR_CalB0_RTFG0_Dspk_GTC_RGB.crf, World Imagery, and Hybrid Reference Layer.
2. On the ribbon, on the Map tab, click Bookmarks. Explore the following bookmarks: Ships, City, Surface Hydrology, Airport, and Shipping Containers.

   

   The bookmarks demonstrate how certain elements in the images are displayed.

   • In the Ships bookmark, the ships are visible in pink and white colors mainly due to double-bounce scattering off the side of the ship.
   • In the City bookmark, the urban structures within the city of Baytown are visible in pink, yellow, and white. The pink and white colors are mainly due to double-bounce scattering off the side of buildings that are oriented perpendicular to the satellite's line-of-sight, and the yellow color is mainly due to double-bounce scattering off the side of buildings that are not oriented perpendicular to the satellite's line-of-sight.
   • In the Surface Hydrology bookmark, the water bodies (lakes and rivers) are visible primarily in blue colors due to single-bounce scattering and some green from residual noise. Around the water bodies, there is land covered by vegetation and rough surfaces visible in light green colors due to volumetric scattering.
   • In the Airport bookmark, the William Hobby Airport tarmac's hard surface is visible in blue due to single bounce scattering.
   • In the Shipping Containers bookmark, the shipping containers are visible in pink and white mainly due to double-bounce scattering off the side of the containers.

   Note:

   Learn about the different types of scattering.

In this tutorial, you processed Sentinel-1 Level 1 SAR imagery to generate an image that is ready for analysis. The workflow included updating orbit data, removing thermal noise, calibrating the data, mitigating speckle, removing radiometric and geometric distortions, and converting the image scaling to a different unit. You then created a color composite to visualize the data in a more meaningful way and examined the resulting image. As an environmentalist working on a Galveston Bay Protection Project in Texas, you are now ready to further examine the SAR imagery to better understand various trends and activities in the bay and the nearby suburbs.

You can find more tutorials in the tutorial gallery.

Acknowledgements

• SAR data (S1B_S6_GRDH_1SDH_20170823T002549_20170823T002612_007060_00C6FB_C69E.SAFE): Copernicus Sentinel-1 data, Aug 23, 2017. Retrieved from ESA Copernicus Open Access Hub, March 23, 2023, processed by ESA.

• Texas_DEM_90m.tif: Copernicus Global Digital Elevation Model (2021) from European Space Agency, Sinergise. Distributed by OpenTopography. https://doi.org/10.5069/G9028PQB. Accessed: May 8, 2023.

• Topographic map sources: Esri, HERE, Garmin, FAO, NOAA, USGS, Intermap, METI, OpenStreetMap contributors, and the GIS User Community
• Imagery Hybrid map sources: Esri, HERE, Garmin, FAO, NOAA, USGS, OpenStreetMap contributors, and the GIS User Community