Evolutionary Architecture Search for Chlorophyll- a Prediction in Lakes using Sentinel-2
The study searched for an optimal machine learning architecture to classify algal blooms using Sentinel-2 satellite imagery from lakes across three European countries. The search found a small, efficient model with 409 parameters that improved classification metrics significantly compared to existing models. This small size makes it ideal for use as a low-cost, onboard screening tool on satellites.