A PyTorch implementation of the Multi-Mode CNN to reconstruct Chlorophyll-a time series in the global ocean from oceanic and atmospheric physical drivers
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Updated
May 18, 2023 - Jupyter Notebook
A PyTorch implementation of the Multi-Mode CNN to reconstruct Chlorophyll-a time series in the global ocean from oceanic and atmospheric physical drivers
Research Derby project to study the connection between MJO, chlorophyll-a, and SST
Monitoring water quality in the Santa Monica Bay using Landsat 8 OLI satellite data.
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.
Launchpad for Sarasota Science and Technology Society (STS) Processing of STELLA Spectrometer, Landsat and PACE Ocean Data
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.
This is a paleolimnological analysis using tidypaleo in R. View the Github page to walk through each step of the analysis.
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