A PyTorch implementation of the Multi-Mode CNN to reconstruct Chlorophyll-a time series in the global ocean from oceanic and atmospheric physical drivers

Combination Of Neural Network models for Estimating Chlorophyll-a over Turbid and clear waters

Launchpad for Sarasota Science and Technology Society (STS) Processing of STELLA Spectrometer, Landsat and PACE Ocean Data

Research Derby project to study the connection between MJO, chlorophyll-a, and SST

We have created a Jupyter Notebook to use with NASA PACE data employing HyperCoast to download the data and then view and process these hyperspectral data using traditional python code. We have also attempted to calculate chlorophyll a too in this notebook that is CoLab ready.

Monitoring water quality in the Santa Monica Bay using Landsat 8 OLI satellite data.

Materials for manuscript describing chlorophyll and hydrology relationships in Tampa Bay

This is a paleolimnological analysis using tidypaleo in R. View the Github page to walk through each step of the analysis.

Scripts to accompany Jones-Kellett & Follows (2025)

Distributory materials for "ML for Aquatic Remote Sensing" sessions at SCOR 2025

Analysis and visualization of water monitoring data collected at VCU's Rice River Center. The script models chlorophyll A concentrations as function of different temperature-based ratios (e.g., temp:discharge) using OLS linear regression, as well as one nonlinear model. Work done in support of Dr. Paul Bukaveckas' lab at VCU.

Final-round Track 2 repository for HydroSat Systems' turbidity and chlorophyll-a inference pipeline in the ITU Ingenuity Cup: AI and Space Computing Challenge 2026.