Geomatica v102 DEM Extraction Tutorial PRISM

7/31/2019 Geomatica v102 DEM Extraction Tutorial PRISM

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Geomatica OrthoEngine v10.2 Tutorial

DEM Extraction of ALOS PRISM Data

ALOS stands for Advanced Land Observing Satellite and was developed by the Japan Aerospace

Exploration Agency (JAXA). The sun Synchronous, Sub recurrent ALOS was launched by JAXA in Januaryof 2006 from Tanegashima Space Center in Japan. The purpose of ALOS was to provide valuableinformation for mapping, precise regional land coverage observation, disaster monitoring, and resourcesurveying. ALOS contains three sensors, commonly referred to as the “three eyes” of ALOS. Thesesensors are: the Panchromatic Remote-Sensing Instrument for Stereo Mapping (PRISM), the AdvancedVisible and Near Infrared Radiometer type 2 (AVNIR-2), and the Phased Array type L-band SyntheticAperture Radar (PALSAR).

The PRISM sensor onboard ALOS contains three independent optical systems that allow for viewing in

the Nadir direction, as well as forward and backward directions. This allows for the production of astereoscopic image along the satellite’s track. PRISM contains 1 band (panchromatic) with a wavelength of0.52 to 0.77 micrometers. The spatial resolution of PRISM is 2.5m (when viewing in the Nadir direction).Swath width of PRISM is 70km when viewing in the Nadir direction, and 35km when in triplet mode. Prism’sspatial resolution makes this sensor particularly desirable for mapping, urban planning, and monitoringdesired areas. PRISM cannot image regions that are beyond 82 degrees North latitude and 82 degreesSouth latitude.

The PRISM sensor contains 6 CCDs for viewing at the Nadir, and 4 CCDs for viewing in the forward andbackward directions. An image file is provided for each CCD when dealing with 1A and 1B1 level imagery(uncorrected imagery). Geomatica software offers support for PRISM imagery levels 1A, 1B1 and 1B2R.It is recommended to use Level 1B1 data because it is radiometrically corrected and is without geometriccorrection.

1.0 Rigorous Modeling

1.1 Initial Project Setup

Start OrthoEngine and click ‘New ’ on the File menu to start a new project. Give your project a ‘Filename ’,‘Name ’ and ‘Description ’. Select ‘Optical Satellite Modeling ’ as the Math Modeling Method. Under Options,select ‘Toutin’s Model ’. After accepting this panel you will be prompted to set up the projection informationfor the output files, the output pixel spacing, and the projection information of GCPs. Enter the appropriateprojection information for your project.



1.2 Data Input

After doing the initial project setup, you need to add both images of the stereo-pair to the orthoengineproject. Under ‘Processing Step ’ goto ‘Data Input ’ and click on ‘Read CD-ROM ’. Select ‘PRISM (LGSOWG)’ as the CD Format and VOL file as the header file. As per the raw imagery, choose the appropriate channelnumber(s). Provide a PIX file name and click ‘Read ’. This will import the raw PRISM data into PIX format

and will add it to the OE project.

The raw PRISM 1A and 1B1 level data is generally distributed in 4/6 tiles. In that case user needs to selectappropriate number of channels while reading-in the data. E.g. if there are 4 tiles in the input dataset withchannel 1, 2, 3 and 4, then user needs to select 1, 2, 3 and 4 as the requested channels.

1.3 Collect GCPs and Tie Points

Select the ‘GCP/TP Collection ’ processing step. GCP collection can be done using various options viz.‘Manual Entry ’, ‘Geocoded Images/Vectors ’, ‘Chip Database ’ or a ‘Text File ’.

For the ALOS PRISM Toutin’s model, a minimum of six accurate GCPs per image (or more, depending onthe accuracy of the GCPs and accuracy requirements of the project) are required. After collecting the Stereo

GCPs / GCPs / TPs, select the ‘Model Calculation ’ Processing Step and click on ‘Compute Model ’. Check‘Residual Report ’ panel (under the Reports processing step) to review the initial results.



1.4 DEM from Stereo: Generate Epipolar Images

When ‘User Select ’ is chosen as ‘Epipolar selection ’, selection of exact left and right image does not matter.Just select any image as ‘Left Image ’ and other image will be added as the right image. Make sure to selectthe image under ‘Right Image ’ box and click on ‘Add Epipolar Pairs to Table ’ to record the pair(s) under Listof ‘Epipolar Pairs ’. If ‘User Select ’ is chosen, repeat the steps until all stereopairs are recorded. In ‘Down Sample Factor ’ put the number of image pixels and lines required to calculate one epipolar image pixel.

For PRISM data, it is also recommended that the user set a down sample factor greater then 1 to obtain amore smooth DEM. For this example, we will use a down sample factor of 2. A value of 4 may also be good.



In ‘Down sample filter ’, click the method used to determine the value of the epipolar image pixel when theDown Sample Factor is greater than 1.Select one of the following:

• ‘Average ’ to assign the average image pixel value to the epipolar image pixel. The average isobtained by adding the image pixel values that will become one epipolar image pixel and dividingthat value by the number of image pixels used in the sum.

• ‘Median ’ to assign the median value of the image pixels to the epipolar image pixel. The median isobtained by ranking the image pixels that will become one epipolar image pixel according tobrightness. The median is the middle value of those image pixels, which is then assigned to theepipolar image pixel.

• ‘Mode ’ to assign the mode value of the image pixels to the epipolar pixel. The mode is the imagepixel value that occurs the most frequently among the image pixels that will become one epipolarimage pixel.

Check off the epipolar pairs under the ‘Select ’ column and then click on ‘Generate Pairs ’. 1.5 Extract DEM

Under the DEM from Stereo processing step, select ‘Extract DEM Automatically’ button.

• In ‘Select ’ column, check off the epipolar pair from which the DEM will be extracted

• Under the ‘Epipolar DEM Extraction Options ’:

Enter ‘Minimum ’ and ‘Maximum ’ elevation values. This elevation range is used toestimate the search area for the correlation. This would increase the speed of thecorrelation and reduce errors.



If the resulting DEM contains failed areas on peaks or valleys, then try increasingthe range.

For ‘Failure ’ value, enter the value used to represent the failed pixels in theoutput DEM. The default is set to be -100

Enter a ‘Background value ’ to represent “No Data” pixels that lie outside theDEM. These pixels are distinguished so that they would not be mistaken forelevation values. The default value is -150.

For ‘DEM Detail ’, specify the level of detail desired for the output DEM. Lowdetail indicates that the process stops during the coarse correlation phase ofaggregated pixels. High detail would mean that the process continues untilcorrelation is performed on images at full resolution.

In the ‘Output DEM channel type ’, enter 16 bit signed. Select the desired ‘Pixel Sampling Interval ’, or sampling frequency. This

parameter controls the size of the pixel in the output DEM relative to the inputimages. The higher the number specified, the larger the DEM pixel will be andthe faster the DEM is processed.

• Under the ‘Geocoded DEM’ ’ section, select ‘Create Geocoded DEM ’ to geocode and merge theepipolar DEMs. However if the DEM is to be edited prior to geocoding, leave this option unselected.If the option is selected, enter a file name for output DEM.

• Click on ‘Extract DEM ’ button.

1.6 Examine Results

Examine the DEM in Focus and continue editing if necessary.

Bad results in the DEM can often be caused by the data, the stereo coverage, the accuracy of the modelgenerated from control points, etc. If there are numerous failed areas that cannot be easily corrected usingthe DEM Editing Tools, then try returning to OrthoEngine and generating epipolar images again or extractingDEM using different parameters (e.g. increase the down scale factor). The PCI Geomatica help files onApplying Tool Strategies for Common Situations in Digital Elevation Models contain more information aboutimproving DEM output.



2.0 Rational Polynomial Coefficients (RPC)

ALOS PRISM stereopair delivered with RPC files can be used for DEM generation using Rational Fucntionproject, in the absence of adequate number of GCPs. Further addition of 1-4 GCPs into your project, inaddition to the delivered RPCs can significantly improve the accuracy of the DEM.

2.1 Initial Project Setup

Start a new project and select the mathmodeling method as ‘Optical Satellite Modeling ’. Under ‘Options ’ select ‘Rational Functions’ (Extract from Image ’ option.

2.2 Stitch Images

While using Rational Function project, stitch the PRISM image tiles by ‘Stitch Image Tiles with RPC ’functionality under ‘Utilities ’ menu. Stitching combines different image tiles into a single PIX file and generatea new RPC for the stitched image.

Browse for image tiles; provide an output PIX file name in the stitching window and click ‘Stitch ’ button. Atthe end of this process, user will be prompted to add-in the final PIX file into the OE project. Click ‘Yes ’ andthe PIX file will be added into the OE project.

Repeat the same stitching activity for the other set of PRISM tiles in the stereo-pair. Double check that both

stitched PIX files are added inside OE project.

2.3 GCP Collection

At this stage an Epipolar / DEM can be directly generated in the absence of any GCPs.

If GCPs are available, they can be added into the project using the same process as defined in section 1.3of this document.

Note: It is recommended to use 1st

order RPC adjustment in a PRISM Rational Function project.



2.4 Generate Epipolar Images and Extract DEM

Generate Epipolar images and extract a DEM using the same steps as described in section 1.4 & 1.5 (underRigorous Model) of this document. Examine the DEM in focus and continue editing if necessary.

Note: The new structure of ALOS PRISM 1B2R data (as shown below) will be supported in future versions of PCI Geomatica.

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Geomatica v102 DEM Extraction Tutorial PRISM