Topic: "chlorophyll-a"
JoanaR/multi-mode-CNN-pytorch
A PyTorch implementation of the Multi-Mode CNN to reconstruct Chlorophyll-a time series in the global ocean from oceanic and atmospheric physical drivers
Language: Jupyter Notebook - Size: 8.97 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 8 - Forks: 2
manhtranduy/Chl-CONNECT
Combination Of Neural Network models for Estimating Chlorophyll-a over Turbid and clear waters
Language: Python - Size: 34.2 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 3 - Forks: 0
CassiaCai/MJO_chlorophyll_a_SST
Research Derby project to study the connection between MJO, chlorophyll-a, and SST
Language: Jupyter Notebook - Size: 9.07 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 0
Philliec459/Launchpad-for-STS-Processing-of-STELLA-Spectrometer-Landsat-and-PACE-Ocean-Data
Launchpad for Sarasota Science and Technology Society (STS) Processing of STELLA Spectrometer, Landsat and PACE Ocean Data
Language: Jupyter Notebook - Size: 2.92 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
Philliec459/STS-Software-to-Download-and-Process-NASA-PACE-Ocean-Ecosystem-hyperspectral-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.
Language: Jupyter Notebook - Size: 147 MB - Last synced at: 12 months ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0
escobar2061/WaterQualityMonitoring_SMB
Monitoring water quality in the Santa Monica Bay using Landsat 8 OLI satellite data.
Language: Jupyter Notebook - Size: 2.58 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
johannabosch/Paleolimnological_Analysis_in_R
This is a paleolimnological analysis using tidypaleo in R. View the Github page to walk through each step of the analysis.
Language: R - Size: 2.81 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
andrewmcameron/modelling-algalBlooms
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.
Language: R - Size: 10.4 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
