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 calibration�correcting 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.
3. Open PCA plugin.
   • Set tm_920526_mul.tif as Input Raster File.
   • Set Number of output Principal Components to 1.
   • Save the Output Raster File as 1992_1.
   • Repeat this procedure for the raster files of 2005 and 2010 and adapt the name of each Output Raster File.

1. Merge the three output raster files with Toolbox --> GDAL/OGR --> [GDAL] Miscellaneous --> Merge