This document discusses change detection techniques using the Orfeo Toolbox. It presents several use cases for identifying changes between images using modules for change detection, SVM classification, and band math. The main challenges are distinguishing exceptional changes from natural changes over time in vegetation. Menus and steps are provided to open and preprocess images, classify changes versus unchanged areas, learn from sample inputs, and refine results.

1. Orfeo Toolbox
Change detection
Stéphane MAY
stephane.may@cnes.fr
orfeo-toolbox.org
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2. Change detection
Goal
Identify changes between 2 images
Main problems
Exceptional change (crisis) mixed with Natural changes
(vegetation evolution)
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3. Monteverdi
Filtering
Change
Detection
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4. Use case 1 : change detection module
Menu File > Open
./img_gloucester_spot_av_ap/Spot5-Gloucester-before.tif
./img_gloucester_spot_av_ap/Spot5-Gloucester-after.tif
Menu > Filtering > Change detection
Click on changed class
➢ Select changed areas
Click on unchanged class
➢ Select unchanged areas
Learn
Display results
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5. Use case 2 : change detection with SVM classif. module
Menu File > Open
./img_gloucester_spot_av_ap/Spot5-Gloucester-before.tif
./img_gloucester_spot_av_ap/Spot5-Gloucester-after.tif
Menu File > Concatenate image
Insert “after channels” first
Menu Learning > SVM classification
Create changed class
Create unchanged class
Learn
Display
Add new areas to refine your results
Option : add features to enhance results (Feature Extraction Module)
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6. Use case 3 : RADAR change detect. with SVM classif.
Menu File > Open
./img_gloucester_av_ap/ERSAvantSmall.png
./img_gloucester_av_ap/ERSApresSmall.png
Menu SAR >Despeckle
Lee filter
➢ Radius 5
Menu File > Concatenate image
Insert crisis image first. Insert before image twice for visualisation.
Menu Learning > SVM classification
Create changed class
Create unchanged class
Learn, Display
Add new areas to refine your results orfeo-toolbox.org
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7. Use case 4 : RADAR change detection with band math
Menu File > Open
./img_gloucester_spot_av_ap/Spot5-Gloucester-before.tif
./img_gloucester_spot_av_ap/Spot5-Gloucester-after.tif
Menu SAR >Despeckle
Lee filter
➢ Radius 5
Menu Filtering > Band math
abs(im1b1-im2b1)
min(im1b1/im2b1, im2b1/im1b1)
Invent your formula !
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8. Use case 5 : classif. based change detection
Menu File > Open
./output_fus1.tif
./output_fus2b.tif
Menu Learning > SVM classification (file1)
Create land cover classes (water, vegetation, soil, roads, houses)
Menu Learning > SVM classification (file2)
Create land cover classes (water, vegetation, soil, roads, houses)
Menu File > Concatenate images (land cover files)
Menu Learning > SVM classification
Create changed class / unchanged class
Learn, Display
Menu filtering > Band math
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Select interesting couples of values from land cover files 8

9. Monteverdi
Thank you for your attention !
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