Episode

Biodiversity Monitoring

Podcast
Data Skeptic
Published
Aug 14, 2024
Duration seconds
1940
Processing state
failed
Canonical source
https://dataskeptic.com/blog/episodes/2024/biodiversity-monitoring
Audio
https://pscrb.fm/rss/p/mgln.ai/e/35/traffic.libsyn.com/secure/dataskeptic/biodiversity-monitoring.mp3?dest-id=201630
JSON
/v1/public/podcasts/data-skeptic/episodes/biodiversity-monitoring
Markdown
/podcast/data-skeptic/biodiversity-monitoring.md

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Summary

In this episode, we talked shop with Hager Radi about her biodiversity monitoring work. While biodiversity modeling may sound simple, count organisms and mark their location, there is a lot more to it than that! Incomplete and biased data can make estimations hard. There are also many species with very few observations in the wild. Using machine learning and remote sensing data, scientists can build models that predict species distributions with limited data. Listen in and hear about Hager's work tackling these challenges and the tools she has built.