Change detection

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This section is still under construction! This article was last modified on 02/1/2016. If you have comments please use the Discussion page or contribute to the article!

Prerequisites of multi-temporal image analysis

1. Acquisition of remote sensing data by the same (or similar) sensor recorded using same spatial resolution, viewing geometry, spectral bands, time of day.
2. Optical calibrationcorrecting uninteresting differences due to illumination, atmospheric conditions, topography, sensor calibration. DNs are converted to physical units (surface reflectance).
3. Clear definitions and classification scheme
4. Exact spatial coregistration

Change detection techniques

Multi-temporal color composites

Principal component analysis

1. Add the raster layers of the years 1992 (tm_920526_mul.tif), 2005 (etm_050623_mul.tif) and 2010 (etm_000515_mul.tif) into a QGIS project. It should be available in the course data.
2. Install PCA plugin under Plugins --> Manage and Install Plugins....
3. Open PCA plugin 25px.
   • Set tm_920526_mul.tif as Input Raster File.
   • Set Number of output Principal Components to 1.
   • Save the Output Raster File as pca1992_1.
   • Repeat this procedure for the raster files of 2005 and 2010 and adapt the name of each Output Raster File.
4. Merge the three output raster files with Toolbox --> GDAL/OGR --> [GDAL] Miscellaneous --> Merge and save Merged output as pca_merge.

Amplitude

1. Add the raster layers of the years 1992 (tm_920526_mul.tif), 2005 (etm_050623_mul.tif) and 2010 (etm_000515_mul.tif) into a QGIS project. It should be available in the course data.
2. Open Toolbox --> OTB --> Miscellaneous --> Band Math.
3. Calculate the amplitude for each raster layer (1992, 2005, 2010) with the use of the bands 5-4-3.
   • For the year 1992, set tm_920526_mul.tif as Input image list.
   • Type sqrt(im1b4^2 + im1b5^2 + im1b3^2) as Expression.
   • Save theOutput image as amplitude1992.
   • Repeat this procedure for the raster files of 2005 and 2010 and adapt the name of each Output Raster File.
4. Merge the three output images with Toolbox --> GDAL/OGR --> [GDAL] Miscellaneous --> Merge and save Merged output as amplitude_merge.

NDVI ratio

1. Add the raster layers of the years 1992 (tm_920526_mul.tif) and 2005 (etm_050623_mul.tif) into a QGIS project. It should be available in the course data.
2. Open Toolbox --> OTB --> Feature Extraction --> Radiometric indices.
   • Set tm_920526_mul.tif as Input Image.
   • Set Red Channel to 4 and NIR Channel to 5.
   • Set Available Radiometric Indices to ndvi.
   • Save the Output Image as ndvi1992.
   • Repeat this procedure for the raster file of 2005 and adapt the name of the Output Image to ndvi_2005.
3. Calculate the ratio of both raster images with the Band Math tool (Toolbox --> OTB --> Miscellaneous).
   • Load ndvi_1992.tif and ndvi_2005 to the Input image list.
   • Type im1b1/im2b1 as Expression.
   • Save theOutput image as ndvi_ratio.