UofA Biological Sciences – GIS
30 November 2009
Supervised Classification in ERDAS ASSUMES PRIOR KNOWLEDGE OF REMOTE SENSING SCIENCE!!! These instructions enable you to perform supervised classifications of multiband imagery in ERDAS software. If your data need preprocessing, please refer to the instruction set on “General Digital Image Utilities in ERDAS.” Some handy resources: Remote sensing text books: Lillesand & Kiefer or Jensen FieldGuide.pdf and TourGuide.pdf C:\Program Files\Leica Geosystems\Geospatial Imaging 9.1\help\hardcopy Webinars (i.e. pre-recorded web seminars) http://www.erdas.com/Resources/Webinars/ArchivedWebinars/tabid/175/Default.aspx The simplified example here classifies Landsat 5 imagery in to 4 desired classes: 1. Water 2. Aquatic vegetation 3. Terrestrial vegetation 4. Bare In your reality you will likely be analyzing for many more and/or different classes! ORIGINAL DATA L5_study.img CREATED DATA Super4max.img Super4min.img Super4.sig
an ERDAS IMAGINE layer stack image file – must contain a minimum of 3 bands
4-class image file output from maximum-likelihood supervised classification 4-class image file output from minimum distance supervised classification signature file for supervised classification
Start ERDAS with the Geospatial Light Table (GLT) Viewer: 1. Click START >>> PROGRAMS >>> LEICA GEOSYSTMES >>> ERDAS IMAGINE >>> ERDAS IMAGINE 1. Select the option to use the Geospatial Light Table (GLT) viewer 2. In the GLT interface, click the OPEN LAYER button (open folder icon) and navigate to your working directory 3. Select L5_study.img and click OK 4. Apply any enhancements to enable you to better interpret the image 5. In the Spectral control select TM Desert Detail 1(or your preference – TM False Natural Color is typically the best choice for vegetation)
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UofA Biological Sciences – GIS
30 November 2009
The example image used here with this particular RGB display shows water as navy, aquatic veg as light blue, terr veg as green, and bare ground as tan 6. Zoom in and out on different areas of the image to get familiar with how the different classes appear 7. Click AOI >>> TOOLS to open the tools you will need for collecting the spectral class signatures
Create Signature File: 8. From the ERDAS main menu bar, click CLASSIFIER >>> SIGNATURE EDITOR 9. Resize/Position the GLT Viewer and Signature Editor windows for optimal simultaneous viewing 10. In the AOI tool dialog, select one of the following CREATE [shape] AOI tools: Rectangle Ellipse Polygon 11. In the viewer (e.g. a zoomed-in area of the imagery where there is a homogeneous area of water), click and drag (rectangle or ellipse tool) or do multiple clicks (polygon) to create an area of interest (AOI) 12. Once you have a dashed outline of the AOI, click the CREATE NEW SIGNATURE FROM AOI button 13. Click once in the new signature class box (e.g. it will say „Class 1‟) and type in a new name; e.g. water1 14. Repeat multiple times in different AOIs that represent the water class in different areas of the imagery – name each new class as „water2,‟ „water3,‟etc. 15. Once you are satisfied with your set of water class signatures, select the rows (click and drag the numbers below the Class# heading) in the Signature Editor and click the MERGE SELECTED SIGNATURES button 16. Delete the old classes (choose EDIT >>> DELETE) and rename the new merged class as simply „water’ 17. REPEAT creating signatures and merging them for the vegetation and bare classes
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UofA Biological Sciences – GIS
30 November 2009
18. Right-click on the symbol below the Color heading to change that class to a different colour (e.g. blue for water, green for terr veg, etc.) 19. Once all four classes are complete, click FILE >>> SAVE 20. Navigate to your working directory and save Super4.sig 21. Analyze the signatures – use the VIEW and EVALUATE tools Click desired row to place ‘>’ pointer beside signature class of interest in display tools
Click to view signature 22. statistics
Click to view plots
Click to view histograms
23. Click any of the display view tools to view quick summaries of your signatures/training sites – the table below provides a briefing of each tool View Tool Name DISPLAY STATISTICS WINDOW
DISPLAY MEAN PLOT WINDOW
DISPLAY HISTOGRAMS WINDOW
Description analyze the statistics for the bands for the current signature to help with evaluations and comparisons view the mean of a single signature or all signatures in all bands of the image to be classified view the histograms of a single or selected signatures for single or all bands
Usage Tip click to activate each signature (indicated by the „>‟) one at a time click to activate each signature (indicated by the „>‟) when in single signature mode click the PLOT button after each change in the control panel
Example of what the histogram windows can look like. Use these display tools to assess the signature classes. Additional evaluation tools are strongly recommended.
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UofA Biological Sciences – GIS
30 November 2009
24. Click EVALUATE >>> CONTINGENCY to view the error matrix for your classes – set parameters and record these to use in the actual classification below 25. COPY/PASTE or SAVE as text file to make omission/commission calculations in MS Excel 26. Click EVALUATE >>> SEPARABILITY to learn of the optimal band combinations 27. COPY/PASTE or SAVE as text file for documentation purposes – useful to help you decide/remember your settings for the actual classification below 28. Edit your signatures as needed or start from scratch if the current ones don‟t appear useful based on the above tools 29. If needed, use the IMAGE INTERPRETER >>> UTILITIES >>> LAYER STACK tool to create a new image containing the optimal band combination as indicated by your SEPARABILITY analyses
Apply Supervised Classification: You can access the supervised classification dialog from the ERDAS main menu bar, click CLASSIFIER >>> SUPERVISED CLASSIFICATION. The following uses the Signature Editor menu. 30. From the Signature Editor menu, click CLASSIFY >>> SUPERVISED 31. Specify the output image; e.g. Super4.img 32. Set all the parameters you want (i.e. what your evaluation tools indicate as being the optimal for class separability) 33. Click OK 34. Once the job state dialog indicates 100% done, click OK 35. REPEAT for a new output if you wish to compare different classification schemes 36. See the section “Visualize the image files” in the General Digital Image Utilities in ERDAS instruction set to simultaneously view the original multispectral RGB and the new classified image
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