Background

This recipe allows the user to create a Digital Elevation Model (DEM) product from two Sentinel-1 SLC scenes. The user first creates an interferogram, and completes the appropriate phase unwrapping steps, then creates the DEM.

Pair Selection for DEMs

ASF’s baseline tool may be used to select a pair of Sentinel images to create the DEM. The baseline tool can be accessed as a stand-alone tool, or via a Vertex search. The optimum pair for DEM creation would have a large perpendicular baseline and a small temporal baseline.

More details for pair selection

Overlap is required. Pairs must be of the same path number and must cover the same area. Images with different flight directions (ascending vs descending) cannot serve as pairs for interferometry.

Coherence is key. You need to pick a pair that has the least temporal baseline possible. This not only minimizes the coherence loss, it also minimizes any potential ground motion. The longer the time between images the higher the decorrelation.

Baseline cannot be ignored. Interferogram sensitivity to the perpendicular baseline is such that a large baseline improves the InSAR’s sensitivity to height variations. So, from that perspective larger baselines are better than smaller. However, as the baseline increases, the coherence decreases. Image alignment is problematic if the perpendicular baseline between images is greater than about 3/4 of the critical baseline because the images will be baseline decorrelated. The critical baseline for S1A is about 5 KM.

Tradeoffs of DEMs created with Sentinel’s C-Band

On the downside, C-band doesn’t penetrate vegetation. This means that DEMs derived from C-band don’t actually measure the earth’s surface, rather they show the top of the canopy. In contrast, an L-band radar with a long wavelength as found on ALOS, can penetrate vegetation. L-band radar receives a reflected wave from the ground and is coherent even in a forest area. C-band has lower coherence than L-band because of the vegetative decorrelation. These effects make it more difficult to make accurate DEMs from Sentinel-1’s C-band than from ALOS’s L-Band.

On the other hand, Sentinel has excellent temporal coverage, meaning that the temporal decorrelation is lower than with previous sensors. Sentinel should be excellent for creating DEMs of barren land or urban areas. However, beware of DEMs created over vegetated areas, especially in the spring during blooming season.

Prerequisites

Materials List

1. Sentinel-1 Toolbox (v6.0.0)
2. Statistical-cost, Network-flow, Algorithm for Phase Unwrapping (SNAPHU) (v1.4.2)
3. ASF’s How to Create an Interferogram Using ESA’s Sentinel-1 Toolbox data recipe
4. ASF’s How to Phase Unwrap an Interferogram data recipe
5. Linux —
   • Windows users can:
     • Download a Linux virtual machine (VM) or
     • Use an Amazon EC2 Linux Instance
6. Sample granules
   • S1A_IW_SLC__1SDV_20150720T203442_20150720T203512_006899_009522_4E7A
   • S1A_IW_SLC__1SDV_20150801T203443_20150801T203513_007074_009A02_3CD7

Steps

Follow steps below from the Create an Interferogram Using ESA’s Sentinel-1 Toolbox data recipe. 

Notice that the Visualize Interferometric Phase — Topographic Phase Removal and Multi-looking and Phase Filtering — Multi-looking steps are deliberately omitted.

• Opening Data in Sentinel-1 Toolbox — Open the Products
• Opening Data in Sentinel-1 Toolbox — View the Products
• Visualize a Band
• Coregister the Data — Coregister the Images
• Interferogram Formation and Coherence Estimation — Form the Interferogram
• Visualize Interferometric Phase — TOPS Deburst
• Multi-looking and Phase Filtering — Phase Filtering

Export to SNAPHU

Export your interferogram or your subset interferogram from Sentinel-1 Toolbox to SNAPHU.

1. In Sentinel-1 Toolbox, navigate to Radar > Interferometric > Unwrapping > Snaphu Export.
   
   In the Snaphu Export window:
    
2. Create a new folder for this step by entering a path and new folder name.
   • Type the folder directory in the Target Folder box.
   • This recipe will call the folder SNAPHU_Export.
3. Select TOPO mode for DEM generation.
4. Select MCF.
5. Change the values of Tile Rows and Tile Columns to 20.
6. Click Run to create the SNAPHU_Export folder.
   • The folder now holds files used for phase unwrapping.

Note: Execution time depends on the size of the interferogram. Unwrapping can use a lot of memory. If the unwrapping fails due to insufficient memory, you may wish to create a subset of your area of interest (See the Create a Subset step of the How to Phase Unwrap an Interferogram data recipe and try again).

   6.  Zip and move the files from the VM to your PC or Mac, so they are accessible to Sentinel-1 Toolbox.

   7.  On your desktop, check your .hdr and .img filenames for a possible mismatch.

• A bug may cause the filename and contents mismatch between the .hdr and .img files.
• Mismatched filenames and contents will cause recipe failure.
• If this happens, see the Defect Warning and Workaround section below.

Defect Warning and Workaround

Workaround: If the polarization in the .hdr filename does not match the .img filename, edit the .hdr filename and contents to match the .img filename and contents polarization.

For example:

• Edit .hdr filename polarization to match the .img filename polarization:
  • UnwPhase_ifg_IW1_VH_20Jul2015_01Aug2015.snaphu.hdr
• To match .img filename:
  • UnwPhase_ifg_IW1_VV_20Jul2015_01Aug2015.snaphu.img
• To get this:
  • UnwPhase_ifg_IW1_VV_20Jul2015_01Aug2015.snaphu.hdr
• Edit the .hdr contents polarization to match the polarization of the .img file.

In some cases, .hdr filenames and files contain the incorrect polarization. If this happens, the import will fail because the .img file will not have a matching .hdr file.

Please scroll up to the Defect Warning and Workaround instructions.

   4.  In the 3-SnaphuImport tab, running Snaphu Import will overwrite your file. To create a new file instead, check the Do NOT save Wrapped Interferogram in the target product option.