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DEM extraction and DSM to DTM conversion

PCI Geomatics -

The following is a brief tutorial showing a step by step procedure for extracting a digital surface model (DSM) from stereo imagery and converting to a digital terrain model (DTM).  In this tutorial, Pleiades 1A imagery was used, however this workflow is similar for DEM extraction from all stereo optical data.

A DSM (also referred to as a DEM) extracted from stereo images represents the earth’s surface and includes all objects on it, for examples, buildings and trees. Many applications require a DTM which represents the bare ground surface without any objects. To convert a DSM to a DTM through manual editing is a very time consuming process. An automatic DSM to DTM conversion program was developed at PCI Geomatics. 

The data used in this tutorial is a sample Pleiades primary data set consisting of panchromatic, multispectral, PMS and tri-stereoscopy images of Melbourne, Australia: https://www.intelligence-airbusds.com/en/23-sample-imagery . A great innovation of the Pleiades system is to offer high resolution stereoscopic coverage capability. The stereoscopic coverage is realized by only a single flyby of the area, which enables collection of a homogeneous product quickly. In addition to the “classical” forward and backward looking stereoscopic imaging, Pleiades can acquire an additional quasi- vertical image (tri-stereoscopy), thus enabling the user to have an image and its stereoscopic environment. In general, a forward and backward looking stereo pair produces the highest accuracy, but this combination's use is limited to areas with gentle terrain. A nadir and forward/backward looking stereo pair can be used in most types of terrain.


Initial Project Setup

1. Open the Geomatica OrthoEngine application.

2. Click File > New

3. Give your project a Filename, Name and Description

  • Select Optical Satellite Modeling as the Math Modeling Method
  • Select Rational Function (Extract from image) under Options
  • Click OK

4. Input the appropriate Output projection and GCP projection information for your project


GCP and DSM Creation

5. Select Data Input as the Processing step

The data to input will be the back scan image and the forward scan image. When viewed in Focus the images will look similar to the images below.

  • Click Open a new or existing image

  • Click New Image
  • Navigate to the location of the data. Select the DIM_PHR1A_XXXXXXXXXX.xml file in the image folder
  • Select Yes when asked if you want to import the data file to a .pix file for optimized processing

  • Select a file name and location for your output .pix file
  • Select Yes when asked if you want to create overviews now
  • Repeat step 5b to 5f to add all images to the project

6. To view the output image select the image from the Open Image window and click Quick Open. Close both windows and move on to step 7

7. In the OrthoEngine toolbar select GCP/TP Collection as the Processing step

  • Select Collect GCP’s Manually, two panels will immediately open (GCP Collection panel and the Open Image panel)

  • In the Open Image panel, click on the first image so it turns blue and click on Quick Open
  • In the Open Image panel, click on the second image so it turns blue and click on Quick Open

  • Adjust the two viewers so that they both can be seen beside each other along with the GCP Collection panel

  • In the GCP collection window select Manual entry as the Ground control source
  • Input a DEM for the data or use demworld.pix found in the etc directory C:\PCI Geomatics\Geomatica 2013\etc
  • Check mark Compute model
  • Collect GCP’s for the image
  • Repeat step 7b- h for all images in the project

Note: Importance of GCPs
A very important step in the DSM extraction workflow is ensuring that you collect very accurate GCPs so that the geometric model of the two images are updated so that when the image models are applied to the imagery, they will accurately align with one  another.

If the two images do not line up during the DSM Extraction process, the output elevation layer may have high levels of error.


8. In the OrthoEngine toolbar select DEM From Stereo as the Processing step

  • Click Create Epipolar Image

  • Select left and right image
  • With both images selected, click the Add Epipolar Pairs To Table button
  • Click Generate Pairs
  • Click OK to the pop-up message that states the epipolar pairs completed successfully
  • Close the Generate Epipolar Images panel


9. In the OrthoEngine toolbar select DEM From Stereo as the Processing step

  • Click Extract DEM automatically

  • Check the epipolar pair by checking the Select box associated with that record

  • In the DEM Extraction Options section, click Apply Wallis filter

Note: The Wallis filter improves the accuracy of the elevation calculation in dark areas, such as buildings and terrain shadow or dark vegetation.

  • Select a Pixel sampling interval of 2
  • Select Create Geocoded DEM
  • Select an output file name and location
  • Set the X and Y resolution to 1 meter for both
  • Click Extract DEM

Note: DEM creation will take a long time as these images have a high resolution.

Pleiades Melbourne extracted DSM



1. Select Focus on the Geomatica Toolbar

2. Open the Algorithm Librarian

  • Select Algorithm Library > PCI Predefined > All Algorithms > DSM2DEM

3. In the DSM2DEM Module Control Panel select the extracted DSM generated from the earlier part of this tutorial

  • Select an output file name and location for the DTM
  • Click the Input Params 1 tab
  • Set the Background elevation value to -150
  • Set Horizontal tile size to 200
  • Click Run

Note: The tile size determines the size of the kernel that will be used to search for local minimum. Generally, a dimension is used that is large enough to remove most buildings and surface features. However, some manual editing is usually required to refine the final product.

Pleiades Melbourne extracted DSM converted to DTM


About the edited DTM
The 1m DTM was generated from the DSM that was displayed earlier. Surface features such as buildings are mostly removed (minimized) by running a DSM2DTM, which searches for local minimum based on a user defined kernel (filter) size. Simple manual editing was performed to remove artifacts in the water and buildings with large XY footprints (not removed by filter), as well as to fix a few bridges.

The DTM is now ready for use in an ortho mosaicking project.

Note: The Pseudo color is based off an equal interval color ramp with about 75 steps, where lower elevations are represented by blue, cyan and light green and moderate to high relative elevations are represented by darker green, yellow, red, purple and white.

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