Massive Change Detection - QGIS plugin

QGIS 2 plugin that applies change detection algorithms on satellite imagery for building reports for urban planning.

Install

Add plugins repository

To install this plugin, you need to add our QGIS Repository first. Go to Plugins -> Manage and Install Plugins.

On the Settings tab, enable Show also experimental plugins, and add a repository named Dymaxion Labs with the following URL:

https://dymaxionlabs.github.io/qgis-repository/plugins.xml

After that, press Reload all repositories button to load our plugins index into QGIS.

Install external dependencies

This plugin makes use of some additional Python dependencies. In a terminal, run the following:

pip install --user fiona numpy opencv-python rasterio shapely

Install plugin

Finally, go to Plugins -> Manage and Install Plugins, and in All or Not Installed tabs, search for Massive Change Detection. Click Install plugin.

Usage

This is a processing plugin, you will have to enable the Processing Toolbox on QGIS to use it properly.

Step 1: Generate change detection raster

The first step is to generate a change detection raster based on two raster images. The algorithm detects changes between the "old"/"before" image and the "new"/"after" image and generates a new binary raster of changes.

Both input rasters must be coregistered and be of the same size and resolution. If you have images of different size and/or resolution, you will need to manually superimpose and clip them first. You can use Orfeo Toolbox to do this (see Superimpose).

Suppose you have two raster layers loaded on QGIS: before.tif and after.tif. Select Massive Change Detection -> Pixel-based algorithms -> Multiband Difference from the Processing Toolbox.

Use before.tif layer on Input old layer and after.tif layer on Input new layer. You can use automatic thresholding (Otsu's method) or manually set a threshold by unchecking Automatic thresholding and choosing a proper value on Threshold value. You can adjust the post-processing filter and its kernel size for better results. Finally click Run to process the image.

Step 2: Build report of changes

The second step is to build a changed lots report based on a vector layer of lots and a change detection raster. Lots vector layer must be in the same projection as rasters.

Select Massive Change Detection -> Report -> Generate changed lots data from the Processing Toolbox.

Use your change detection raster (already generated on Step 1) on Input change detection layer, select one of your input raster images (before.tif, or after.tif) on Input image layer. Then set your lots vector layer on Input lots vector layer field, and select the lot id field on Lot id field.

The selection threshold is related to the percentage of detected change in a particular lot. For example, 0.5 means that a lot that has changed more than 50% of its area is marked as changed.

This algorithm will generate both a new vector layer of changed lots and a table (CSV) layer.

Development

Clone the repository inside your QGIS plugin directory. On Ubuntu this would be ~/.qgis2/python/plugins/:

cd ~/.qgis2/python/plugins/
git clone https://github.com/dymaxionlabs/massive-change-detection
cd massive-change-detection

Install packages for test and code coverage.

pip install --user -r requirements.txt

If you have installed QGIS from source use scripts/run-env-linux.sh to set up the environment variables so that Python can find QGIS inside your virtual environment. For example, if it is /opt/qgis2:

source scripts/run-env-linux.sh /opt/qgis2

Run tests and build code coverage reports with make test.

I18n

You can find the list of supported locales is in the LOCALES definition on Makefile. If you want to add a new language, you have to add it there first.

Prepare translations strings with make transup. This command will search all translated strings in the repository and generate .ts files.

Edit the translations files (files ending in .ts) in i18n/.

Finally compile translation strings with make transcompile.

Issue tracker

Please report any bugs and enhancement ideas using the GitHub issue tracker:

https://github.com/dymaxionlabs/massive-change-detection/issues

Feel free to also ask questions on our Gitter channel, or by email.

Help wanted

Any help in testing, development, documentation and other tasks is highly appreciated and useful to the project.

For more details, see the file CONTRIBUTING.md.

License

Source code is released under a GNU GPL v3 license. Please refer to LICENSE.md for more information.