This notebook was composed for the "Remote Sensing" class of "Environmental Data Science" (EDS 220) at the University of California Santa Barbara in Fall 2021. It provides an introduction to using high frequency radar (HFR) data from the Integrated Ocean Observing System network to derive surface current velocity and direction in the Huntington Beach area during the recent oil spill. Predicting how oil will move in real time is crucial for agencies responding to oil spill emergencies. Real time data acquistion is important to ensure that resources are spent in a targeted and efficient manner, and that reliable information can be shared with the public to reduce the threat to life and livelihood. Compiling an animated map as a manner of convenient visualization, this projects shows how public real-time data can be used to better mitigate and respond to oil spills.
Here, we utilize 6 km resolution (hourly) HFR data of surface currents and oil blob movements over time with data provided by the Coastal Observing Research and Development Center at Scripps Institution of Oceanography, UCSD and the Environmental Response Management Application (ERMA), respectively.
The Python code is wrapped in a Jupyter notebook for convenient explanations and code aside. Data is mainly wrangled using xarray and geopandas. Plotting and animations are done by matplotlib and contextily.
The easiest way of running the data in a clean Jupyter Notebook environment using the provided Binder instance. Just click the button below and it starts a new Binder instance for you. In case you want to use your own environment, you are free to do that as well!
IMPORTANT: In order to get the animations right, you must make sure to run the Notebook within a JupyterNotebook instead of a JupyterLab instance. You can do so by replacing the URL suffix */lab/tree/HFR_Surface_Current_CodeAlong.ipynb to */notebooks/HFR_Surface_Current_CodeAlong.ipynb after the Jupyter Instance has loaded successfully.
↑↑↑↑↑↑↑↑↑↑↑↑↑↑↑ click the binder icon above to begin. A remote python session will launch in your browser with the tutorial. Be patient, sometimes it takes a while for the session to initalize the first few times.
Are you getting a weird "Javascript Error: IPython is not defined" error message? That is probably because your notebook is run within a JupyterLab instance instead of a JupyerNotebook instance. See hints in the section above to get rid of this problem!
If you have any issues or questions, please feel free to contact any of us via the contact information given in the GitHub profiles.