Predictive Foobar: new method for predicting Foobar Hackosa spawning events using Argos
math goes here
Project idea: brief description of project goal or focus
Pitch + Ideation: �Fill in these once you start discussion so others can chime in
Build the project team:�Fill in these once project group is somewhat established
Other content to help people understand the project!
Inertial oscillations in the marginal ice zone
This project will satellite imagery to track inertial oscillations at the sea ice edge. These currents are driven by storms and contribute to ocean mixing.
1) Source and plot satellite imagery
2) Apply object tracking algorithm
3) Learn about ocean currents
Tools and skills: Imagery
Acquiring and plotting imagery from multiple platforms.
Satpy seems useful!
Tools and skills: Floe tracking
Image processing and computer �vision methods for tracking
OpenCV’s Optical Flow seems useful!
Team members: �Laura C. (Seattle in-person)�Dalton KS (virtual) … Aditya Sharma (Australia in-person)
The main idea of this project is to automate the process of identifying a possible oil slick in a satellite image, cropping the area of interest to then start validating whether it is oil or a look-alike.
2) Histogram and statistical analysis to find the possible oiled area
3) Crop the area of interest and start validations
Project idea: Oil spill Monitoring: Segmentation of Satellite Imagery
Project idea: Mooring processing and data page 📜
Pitch + Ideation: We want to develop some data visualization tools for mooring data in Puget Sound and La Perouse Bank. Ideally, these could be interactive plots, hosted on Github Pages, where users could explore the data on their own. The learning goals are to improve skills in Github pages, data interactivity, and data visualization�Zoom breakout room #❓🔮
Build the project team:�Github repo: https://github.com/oceanhackweek/ohw-fancymoorings
Project idea: Marine Species Distribution Modeling tutorial: sea turtles
There are many Species Distribution Model (SDM) tutorials for land applications and the applications for marine SDMs from marine reserves or fishing zones, evaluating impacts of human use of the ocean, estimating fish densities. However there are almost no marine SDM tutorials available. A few basic tutorials with marine examples would be very helpful for people who want to learn how to create marine SDMs and could be used for future OceanHackweeks. Eli Holmes (who pitched idea) will use this in an upcoming Ocean hackweek in India in Sept 2023. She has a ‘analysis ready zarr file’ with environmental variables that we can use for the Arabian Sea and Bay of Bengal.
Proposed tutorial (Jupyter notebook or Rmarkdown file) with code:
Project team pages
SDM example
Project idea: SST spatial distribution prediction using machine learning
Pitch + Ideation: Predict SST anomalies (upwelling, etc), generate SST spatial distribution, the model can also be used with other type of data as input! We plan to use satellite data (MUR)
STEPS:
Build the project team:�Github repo: URL: https://github.com/oceanhackweek/ohw23_proj_sst/
Machine Learning for Argo Data QC
PROJECT: Apply a ML Approach for Argo Data QC to improve the quality of the data
HOW:
Build the project team:�Github repo: URL: https://github.com/oceanhackweek/ohw23_proj_argo_ml
Goal: Better determination of suspicious data in Argo Data
Project: Benthic habitat mapping (image processing/seabed classification)
Pitch + Ideation: Habitat Mapping using Irish national seabed mapping program INFOMAR multibeam echosounder data- bathymetry and backscatter data and utilise a range of machine learning techniques in SciKit-Image Python library.
Start off simple to increasingly complex models and utilise the confusion matrix for accuracy assessment.
Possible habitats include coral reefs, continental shelf or slope or more exciting environments from national seabed mapping data!!
Build the project team:
Aim for Tuesday: Get data loaded to Jupyterhub shared folder
Direct Georeferencing of Drone Images
Using drones over the ocean makes it difficult to use structure Shallow water areas we can use structure from motion (SfM), in deeper water with waves SfM fails.
Is this the same turtle?
Where is this rock?
Where is this point in a 10m satellite pixel?
Investigating the variability of the suppression of the South Australian upwelling.
Context: Playing with the IMOS mooring data in the past Ocean Hack, I noticed a suppression of South Australian upwelling that lead to a question:
What is the variability of the South Australian upwelling and what is driving it?
Passive acoustics project: linking soundscape metrics with other ocean variables
Idea/pitch: use open access acoustics datasets and extract some acoustics metrics from the soundscape. Then fetch some other variables available for the same locations to explore links and correlations.
Steps:
Project Idea: Compare Different Bioinformatic Pipelines to Produce Standardized Output For Amplicon Sequence Data
Does The Pipeline Chosen Affect The Biological Interpretation?
Possible Pipelines that are available on GitHub using different tools:
Could possibly be incorporated into the Species Distribution Modelling Idea (US Proposed); - will the differences in bioinformatic pipeline chosen lead to difference in species distribution; eDNA data becomes the biological input data into the species distribution maps
Data integration: incorporate abiotic factors into analyses; ideally depth, habitat and other relevalent abiotic variables
Goal for Wednesday: demultiplex data, upload it to the cloud, create samplesheets for different pipelines, run pipelines, identify problems/bugs.
Clustered image map showing integration between 16S data and abiotic parameters. Source: http://mixomics.org/mixkernel/