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Hackathon for Biodiversity

This repo contains some data cleaning scripts, data dumps, and assets for the first Hampton Roads Datathon from September 9 to September 16, 2022. The hackathon was hosted by Slover Library in Norfolk, Virginia. The theme of the hackathon was "Analyzing, Promoting, and Protecting Biodiversity in Hampton Roads".

website graphic

Website

We developed a web application using React component kepler.gl to show trends in bird distribution throughout the Hampton Roads region. There is a separate repo for the web app.

time gif

Presentation

The following presentation was given alongside the web application demonstration.

Data

We used data from the FeederWatch raw dataset, information on native birds from the Virginia Society of Ornithology, and images from Wikimedia Commons.

Scripts

Data cleaning

This script reduced the raw dataset of Feederwatch into a state of VA and Hampton Roads dataset. Apache Arrow (parquet) is used to compress output file size. The final out_data.csv is used in webapp.

  • FIA Data

(Data not used) The pull_fia_data.R script pulls data from FIA. It's a workaround given FIA had website issues circa Sept 2022. main_fia.py outputs cleaned data into a form usable for mapping.

This script was to clean the list of VA birds and assign a "native" or "non native" class.

(Data not used) This script was to clean the VA Conservation data into "native"/"non native", but data was limited to only species in VA with a noted conservation status.

Analysis

  • Bird's Eye Stats

hamptonroads_stats.R - calculate misc statistics for presentation about land coverage.

  • iNaturalist density by city

(Data not used) Look at density of birds by city/county with two scripts: inaturalist_data_density.py and inaturalist_data.ipynb.

  • Summarize bird details

summarize_bird_stats.R calculates year-over-year trend information and calculates a 'conservation score' reflecting the regional data. summarize_vabird_dets.R pulls image/description from Wikipedia, integrates detail on nativity, and the statistics of each species into one dataframe. Exports as out_infobox.csv for webapp.

Logo

We made our beautiful logo using Stable Diffusion. Introducing Mr. Mallard.

Contact

Feel free to contact Richard Latham for further information.

This was a team effort! The team consisted of: Marti McElreath (web application developer), Raymond Hear (data cleaning and presentation development), Lakshmi Podagatlapalli (data cleaning and presentation), Richard Latham (data cleaning and presentation development).