The Colour Pattern Regression (CPR) algorithm complement for QGIS is presented for determining and quantifying the relationship between aerial images and raster maps. Aerial images can be readily decomposed into their standard RGB spaces that assign numerical values to their colours. According to them, a linear regression can be established to correlate raster values with the colour patterns, and if the model performance is considered satisfactory, the final result will provide a raster interpolation with finest resolution according to colour nuances within the aerial image. The CPR Algorithm allow both, the calculation of the regression coefficient and the evaluation of the goodness of fit of the model. The use of the CPR-QGIS plugin could enable the study of the relationships of aerial images and earth surface products – e.g. soil moisture content, landcover, vegetation and forests, soils, urban heat islands – or marine products – e.g. chlorophyll, total suspended solids. The tool is open source and will be readily adapted with additional features and improved general performance ratings thresholds for the physical problems to be solved.The Colour Pattern Regression (CPR) algorithm complement for QGIS is presented for determining and quantifying the relationship between aerial images and raster maps. Aerial images can be readily decomposed into their standard RGB spaces that assign numerical values to their colours. According to them, a linear regression can be established to correlate raster values with the colour patterns, and if the model performance is considered satisfactory, the final result will provide a raster interpolation with finest resolution according to colour nuances within the aerial image. The CPR Algorithm allow both, the calculation of the regression coefficient and the evaluation of the goodness of fit of the model. The use of the CPR-QGIS complement could enable the study of the relationships of aerial images and earth surface products – e.g. soil moisture content, landcover, vegetation and forests, soils, urban heat islands – or marine products – e.g. chlorophyll, total suspended solids. The tool is open source and will be readily adapted with additional features and improved general performance ratings thresholds for the physical problems to be solved.
- Download the last version available "last_version.zip".
- Open QGIS v3.x.
- Select Plugins\Manage and Install Plugins
- Select the option Install from ZIP.
- Browse the route to the “last_version.zip” file and press the install button.
- Area of interest (shp): Defines the outer interpolation polygon with a shape file.
- Area for calibration (shp): Defines a sub-polygon with a shape file for calculation of the initial values.
- Aerial image input: A three-banded (RGB) raster map with the aerial image of the study area.
- Raster data input: A raster map with the numerical values that can be correlated with colours.
- Results folder: Defines the calculations route.
- Variability RGB: Defines the variability around the initial RGB values for the high-resolution loop calculation.
- Initial values loop variability: Number of iterations that will be carried out for the calculation of the initial RGB values in the calibration area.
- High resolution loop variability: Number of iterations that will be carried out for the calculation of the final RGB values in the interest area.
- Performance statistics thresholds: Defines the thresholds for Very good, Good, Satisfactory and Unsatisfactory performance for the statistics NNSE, KGE and PBIAS.
- RGB Coefficient: Present the calculated RGB parameters of the linear regression.
- Statistics performance (%Area): Presents the percentage of area from every model performance type defined in the Calculations section for the statistics NNSE, KGE and PBIAS.
The information provided includes the necessary information to reproduce an example of the correlation between the aerial image from Sentinel 2 and a raster map of Total Suspended Matter (TSM) from Sentinel 3.
In this case, Mar Menor lagoon area was selected as part of the H2020 SMARTLAGOON project (GA 101017861).
- Create or upload files
- Add files using the command line or push an existing Git repository with the following command:
cd existing_repo
git remote add origin https://github.com/vielca/CPR
git branch -M main
git push -uf origin main
This work has been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017861 and by the Ramon y Cajal Grant RYC2018-025580-I, funded by MCIN/AEI/ 10.13039/501100011033 and “ERDF A way of making Europe” and FSE invest in your future.
Moreover, authors acknowledge Vicente M. Candela Canales for supporting the R&D investment and programs within the Vielca companies.