Pleiades 1A data DEM extraction and DSM to DTM conversion Geomatica 2015 Tutorial

Transcription

1 Pleiades 1A data DEM extraction and DSM to DTM conversion Geomatica 2015 Tutorial 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 is limited to areas with gentle terrain. A nadir and forward/backward looking stereo pair can be used in most kinds of terrain. 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. Geomatica 2015 comes with an enhanced DSM extraction from stereo imagery algorithm. The algorithm is capable of generating high quality high resolution DSM and DTMs from stereo pairs. The following is a brief tutorial showing a step by step procedure for extracting a digital surface model (DSM) and creating a digital terrain model (DTM) from Pleiades 1A imagery. 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. The steps in this tutorial can be followed using any Pleiades 1A imagery. A sample Pleiades Tristereo dataset can be downloaded from the link below: Initial Project Setup 1. Open the Geomatica 2015 OrthoEngine application. 2. Open OrthoEngine a. Click File > New Page 1

2 3. Give your project a Filename, Name and Description a. Select Optical Satellite Modeling as the Math Modeling Method b. Select Rational Function (Extract from image) under Options c. 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 backward looking image and the forward looking image. When viewed in Focus the images will look similar to the images below. If you are working with your own dataset, please note that you will want to select 2 stereo images, not all 3. You should select the 2 images based on the type of terrain in your images. In general, a forward and backward looking stereo pair produces the highest accuracy, but this combination is limited to areas with gentle or flat terrain. A nadir and forward/backward looking stereo pair can be used in most kinds of terrain. Page 2

3 a. Click Open a new or existing image b. Click New Image c. Navigate to the location of the data. Select the DIM_PHR1A_XXXXXXXXXX.xml file in the image folder. d. Select Yes when asked if you want to import the data file to a.pix file for optimized processing e. Select a file name and location for your output.pix file f. Select Yes when asked if you want to create overviews now g. 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 Open. Close both windows and move on to step 7. Page 3

4 7. In the OrthoEngine toolbar select GCP/TP Collection as the Processing step a. Select Collect GCP s Manually Two panels will immediately open: the GCP Collection panel and the Open Image panel b. In the Open Image panel, click on the first image so it turns blue and click on Open c. In the Open Image panel, click on the second image so it turns blue and click on Open d. Adjust the two viewers so that they both can be seen beside each other along with the GCP Collection panel Page 4

5 e. In the GCP collection window select Manual entry as the Ground control source f. Input a DEM for the data or use demworld.pix found in the etc directory C:\PCI Geomatics\Geomatica 2015\etc g. Check mark Compute model h. Manually collect GCP s for the image i. Repeat step 7b- h for all images in the project 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 a. Click Create Epipolar Image a. Select left and right image b. With both images selected, click the Add Epipolar Pairs To Table button c. Click Generate Pairs Page 5

6 d. Click OK to the pop-up message that states the epipolar pairs completed successfully e. Close the Generate Epipolar Images panel 9. In the OrthoEngine toolbar select DEM From Stereo as the Processing step a. Click Extract DEM automatically b. Check the epipolar pair by checking the Select box associated with that record c. In the DEM Extraction Options section, click Apply Wallis filter Wallis Filter The Wallis filter improves the accuracy of the elevation calculation in dark areas, such as buildings and terrain shadow or dark vegetation. Page 6

7 d. Select Create Geocoded DEM e. Select an output file name and location f. Set the X and Y resolution to 1 meter for both g. Click Extract DEM Note: DEM creation will take a long time as these images have a high resolution. Figure 1.0: Pleiades Melbourne extracted DSM Page 7

8 DSM to DTM 1. Select Focus on the Geomatica Application Bar 2. Open the Algorithm Librarian a. Select Algorithm Library PCI Predefined All Algorithms DSM2DTM Page 8

9 3. In the DSM2DTM Module Control Panel select the extracted DSM generated from the earlier part of this tutorial a. Select an output file name and location for the DTM b. Click the Input Params 1 tab c. Set the Elevation failure value to -150 d. Set Object size to 200 e. Click Run Tile Size 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. Page 9

10 Figure 2.0: 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. Page 10