There are 0 repository under harmful-algal-blooms topic.
Planktos is an image recognition model tailored for classifying various species of phytoplankton. Built using cutting-edge machine learning algorithms, this tool enables researchers and environmentalists to automate and accelerate the identification process, enhancing studies in marine biology and ecology.
Datasets from "Optimal growth conditions of the haptophyte Chrysochromulina leadbeateri causing massive fish mortality in Northern Norway"
Snakemake pipeline to reproduce the results in the forthcoming paper "One week ahead prediction of harmful algal blooms in Iowa lakes"
An ensemble-based machine learning approach for predicting corrected Chlorophyll-a concentrations, trained with real historical data and enhanced by synthetic data generated using agents with LLM, providing a scalable and cost-effective solution for early detection of harmful algal blooms (HABs).
Oceanographic bulletins for the West Florida Shelf produced from regular cruises
A remote sensing study in the reproducible research framework