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DalinJiang/EO-Africa-SWAM

Domaine:

environment and energygeospatial

Type de record:

software
Créateur:
Dal
Hôte:
This repository includes codes that developed and used during the ESA EO-Africa SWAM project. # EO-Africa R&D SWAM **SWAM**, stands for "*Sentinel 2 user-relevant water quality monitoring in small southern African water bodies*", is an European Space Agency (ESA) EO-Africa (eoafrica-rd.org) funded research project. SWAM aimed to use the Sentinel-2 Multi-Spectral Instrument (MSI) high spatial resolution imagery to monitor water quality variables including chlorophyll-a (Chla) and total suspended matter (TSM) concentrations in small inland water bodies in the Western Cape Province, South Africa. As a starting point, the project focused on six lakes and reservoirs that are key for drinking water, irrigation, biodiversity, and recreation, including: * Clanwilliam Dam (CW) * Misverstand Dam (MV) * Voëlvlei Dam (VV) * Theewaterskloof Dam (TW) * Zeekoevlei (ZV) * Rietvlei (RV) This repository includes the Python code that were developed and used during the SWAM project for Chl-a and TSM monitoring from Sentinel-2 MSI imagery. ## 1. Chl-a ### (i) Algorithm Chl-a concentration products were produced using the ACOLITE-RAdCor atmospherically corrected (Vanhellemont & Ruddick 2016; Castagna & Vanhellemont, 2025) remote sensing reflectance product, and then deriving Chl-a using the Mixture Density Network (MDN) from Pahlevan et al (2020). ### (ii) Requirements Make sure that you have either cloned or copied an ACOLITE installation (we used acolite20250402) into your working directory, following the installation instructions from the acolite github repository. You would also need to clone MDN-STREAM, with useful instructions for setting up the appropriate conda environment provided at MDN_tutorials. ## 2. TSM ### (i) Algorithm TSM concentration products were produced using the remote sensing reflectance that is derived from the Case 2 Regional CoastColour (C2RCC) atmopsheric correction processor (Brockmann et al., 2016) with the C2X-Complex neural network, and then deriving TSM using the Jiang et al (2023) algorithm with re-calibrated coefficients. # …

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Licenses

GPL-3.0