8.21. ASTER

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a Japanese instrument. ASP can process ASTER Level 1A VNIR images. These are acquired with a stereo rig consisting of two cameras, pointing nadir and back. The orbit is sun-synchronous, at an elevation of 705 km. The ground sample distance is 15 meters/pixel.

See a ready-made ASTER example. It has the input images and cameras, ASP outputs, and instructions for how to run it. Also see a workbook with illustrations.

ASP can correct for the jitter in these cameras (Section 16.38.11).

8.21.1. Fetching the data

ASTER satellite images are freely available from:

When visiting that page, select a region on the map, search for AST_L1A, and choose ASTER L1A Reconstructed Unprocessed Instrument Data V004.

If too many results are shown, narrow down the choices by using a range in time or deselecting unwanted items manually. Examining the data thumbnails is helpful, to exclude those with clouds, etc. Then click to download.

As of end of 2025, the products can only be downloaded in the HDF-EOS format, which requires an ASP build from 2026-01 or later (Section 2.1).

Note that some datasets may not contain the bands 3B and 3N needed for stereo.

The EarthData web site also offers pre-existing ASTER Global DEM (GDEM) products.

8.21.2. Data preparation

In this example we will use the dataset:

AST_L1A_00404012022185436_20250920182851.hdf

around the San Luis Reservoir in Northern California.

This dataset contains all image data and metadata in single .hdf file. It can be extracted with aster2asp (Section 16.2) as:

aster2asp input.hdf -o out

Older V003 datasets were provided as zipped files containing data directories with TIFF images and metadata as text files. In that case, after the data is extracted, the preparation command is:

aster2asp dataDir -o out

In either case, four files would be produced, named:

out-Band3N.tif out-Band3B.tif out-Band3N.xml out-Band3B.xml

We refer again to the tool’s documentation page regarding details of how these files were created.

Open the images in stereo_gui (Section 16.72) as:

stereo_gui out-Band3N.tif out-Band3B.tif

and ensure that they are of good quality, or else get another dataset.

8.21.3. Stereo with raw images

As of build 2026/3 (Section 2.1), ASTER data are always processed with the CSM model (Section 8.12).

Run parallel_stereo (Section 16.51):

parallel_stereo -t aster         \
  --stereo-algorithm asp_mgm     \
  --subpixel-mode 9              \
   out-Band3N.tif out-Band3B.tif \
   out-Band3N.xml out-Band3B.xml \
   out_stereo/run

This uses the asp_mgm algorithm, which is the most accurate algorithm ASP has. One can also try the option --subpixel-mode 2 which will be much slower but produce better results.

See Section 6 for a discussion about various stereo algorithms and speed-vs-quality choices.

This is followed by DEM creation with point2dem (Section 16.56):

point2dem -r earth --auto-proj-center \
  out_stereo/run-PC.tif

This will create a DEM named out_stereo/run-DEM.tif using an auto-guessed local UTM or polar stereographic projection (Section 16.56.1), with an auto-guessed resolution (about 15 m / pixel, the image ground sample distance).

Visualize the DEM with stereo_gui (Section 16.72):

stereo_gui --hillshade out_stereo/run-DEM.tif

8.21.4. Stereo with mapprojected images

To improve the results for steep terrain, one may consider doing stereo as before, followed by mapprojection onto a coarser and smoother version of the obtained DEM, and then redoing stereo with mapprojected images (per the suggestions in Section 6.1.7).

Initial stereo:

parallel_stereo -t aster         \
  --stereo-algorithm asp_mgm     \
  --subpixel-mode 9              \
   out-Band3N.tif out-Band3B.tif \
   out-Band3N.xml out-Band3B.xml \
   out_stereo/run

Create a low-resolution smooth DEM at 200 meters/pixel:

point2dem -r earth --auto-proj-center \
  --tr 200 out_stereo/run-PC.tif      \
  -o out_stereo/run-200m

Mapproject onto this DEM at 15 meters/pixel:

mapproject --tr 15               \
  out_stereo/run-200m-DEM.tif    \
  out-Band3N.tif out-Band3N.xml out-Band3N_proj.tif
mapproject --tr 15               \
  out_stereo/run-200m-DEM.tif    \
  out-Band3B.tif out-Band3B.xml out-Band3B_proj.tif

Run parallel_stereo with the mapprojected images:

parallel_stereo -t aster                  \
  --stereo-algorithm asp_mgm              \
  --subpixel-mode 9                       \
  out-Band3N_proj.tif out-Band3B_proj.tif \
  out-Band3N.xml out-Band3B.xml           \
  out_stereo_proj/run                     \
  out_stereo/run-200m-DEM.tif

Create the final DEM:

point2dem -r earth --auto-proj-center \
  out_stereo_proj/run-PC.tif

It is very important to use the same resolution (option --tr) for both images when mapprojecting. That helps making the resulting images more similar and reduces the processing time (Section 6.1.7.4).

One could consider mapprojecting at a higher resolution, for example, at 10 meters/pixel.

It is suggested to also create and inspect the triangulation error image (Section 16.56). If it is large (comparable to ground sample distance), the cameras should be bundle-adjusted first (Section 16.5).

See Fig. 16.18 for an illustration.

8.21.5. Stereo with ortho-ready L1B images

ASTER L1B images are also available. These are produced by projecting L1A images onto the WGS84 ellipsoid at zero elevation. ASTER L1B images can be processed with ASP using the workflow for ortho-ready images (Section 6.1.7.9).

Invoke parallel_stereo with the L1B images (already mapprojected), L1A cameras, output prefix, and the option --ortho-heights 0 0. The results are nearly the same as obtained with L1A images.

8.21.6. The CSM model

An ASTER camera model consists of a sequence of satellite position samples and a set of camera directions (sight vectors, in world coordinates), sampled at about a dozen image rows and columns.

ASP fits a CSM linescan model (Section 8.12) on-the-fly to the ASTER sight vectors and satellite positions. Instead of a set of directions on a grid, there is one camera orientation at each satellite position sample. This enables solving for jitter in ASTER cameras (Section 16.38.11).

The CSM model is produced by optimizing the optical center, focal length, and camera orientations, to fit best the provided ASTER sight vectors. No ground information is used, or stereo pair knowledge. The satellite positions do not change.

The bundle adjustment program (Section 16.5) will optimize and save the produced CSM models (Section 8.12.6). To save the best-fit CSM models with no further refinement, invoke this tool with zero iterations.

The CSM model may be further refined by tying together multiple datasets and using ground constraints (Section 12.2.2).

8.21.7. Using the RPC model

ASTER XML files also contain RPC coefficients. These can be used with -t rpc (Section 8.23) instead of -t aster. The RPC model is an approximation and less accurate than the exact linescan model described above. Use the exact model (-t aster) for best results.