This python script uses Sentinel-2 products (L2A) to display the spatial distribution of three relevant indicators of eutrophication: chlorophyll-a, turbidity, secchi disk transparency.
Feel free to open a pull request to add a new eutrophication algorithm to the script.
In order to run this script you need to have the following dependencies installed on your local machine:
- numpy and osgeo (gdal, osr), matplotlib
python -W ignore main.py in="c:\Users\<your_username>\Desktop\data" shape="c:\Users\<your_username>\Desktop\lake_shape.shp" statistics plotin=path to the sentinel-2 data folder- if you'd like to clip your region with a polygon then reference the path to your shapefile
shape=(shape and satellite data must have the same crs) statisticsadd this flag if the mean, min, max, variance and standard deviation should be calculatedplotadd this flag to create a subplot with the three water quality parameter-W ignoreto ignore numpys "RuntimeWarning: divide by zero encountered" error message
Make sure your data folder contains only the Sentinel-2 data with the original folder structure. The processed folder will be
created by the script.
data
└───S2A_MSIL2A_20200217T190441_N0214_R013_T10SEJ_20200217T230414.SAFE
└───S2A_MSIL2A_20200414T184921_N0214_R113_T10SEJ_20200414T230546.SAFE
└───S2B_MSIL2A_20200618T184919_N0214_R113_T10SEJ_20200618T224552.SAFE
└───...
└───processed
The path to the image data should be as follows GRANULE -> L2... -> IMG_DATA.
- [1]: Grendaite et al., 2018. Chlorophyll-a concentration retrieval in eutrophic lakes in Lithuania from Sentinel-2 data. Geologija. Geografija 4 (1), 15-28.
- [2]: Esri, 2021. River Turbidity Estimation using Sentinel-2 data, https://developers.arcgis.com/python/sample-notebooks/river-turbidity-estimation-using-sentinel2-data-/
- [3]: Delegido et al., 2019. Turbidity and Secchi disc depth with Sentinel-2 in different trophic status reservoirs at the Comunidad Valenciana