Satellite Imagery Approach in the H2020 SMARTLAGOON Project

Are you familiar with the products of the European Space Agency’s (ESA) Copernicus programme?

We are using both Sentinel-3 (S3) and Sentinel-2 (S2) in SMARTLAGOON because we are interested in using the almost daily remotely sensed water quality data to calibrate our Mar Menor lagoon model, which is provided by S3, but unfortunately at a very low resolution – i.e. 300 m pixels. We realised that in such a context, in a shallow water lagoon, there is a clear relationship between aerial images – such as those provided by S2 every 5-10 days and with a resolution of up to 10 m pixels – and the Total Suspended Matter (TSM) product derived from the S3 bands.

However, to the best of our knowledge there was no toolbox that could determine the existing relationship, so we developed the Colour Pattern Regression (CPR) algorithm, which correlates the colour (Red, Green and Blue) bands of the S2 products with the numerical grid information of the S3 products using three constants – i.e. R, G and B – that multiply the matrix information of the corresponding bands.

The CPR algorithm is intended to be an open source software and tool, so it is available for download from the official QGIS repository – within the QGIS menu bar, select Plugins, Manage and Install Plugins… and then search for CPR and proceed to install it – and the latest version of the code is also available from https://github.com/vielca/CPR.

For a description of the product, see P. Blanco-Gómez et al, CPR Algorithm-A new interpolation methodology and QGIS plugin for Colour Pattern Regression between aerial images and raster maps. SoftwareX (2023) 101356, https://doi.org/10.1016/j.softx.2023.101356.

Finally, the following image shows the downscaling results of applying the CPR algorithm to the S3-TSM product with the S2 and Landsat 8 aerial images during the last 15 days of September 2023, using the Mar Menor context both for calibration and as an area of interest.