Figure 4.

Suggested HAB ML/AI workflow for the data collection, integration, and development of a HAB ML/AI model to enable the development and understanding of an integrated picture of the cyanoHAB dynamic ecosystem. Multisource HAB data that spans the different meteorological spatial scales and temporal resolutions (as defined in section 4) should be curated and used to train, test, and validate ML models. The model should then be analyzed to enable extraction of key insights, in terms of the relative feature importance quantification and generation of design maps for cyanoHAB formation. The model development and analysis should be conducted iteratively to ensure a robust model. Insights and predictions obtained from such an adaptive framework will then be interpreted by domain experts and decision-makers.