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January 25, 2023 24 mins

On this episode of Through the Human Geography Lens, hosts Terri Ryan and Gwyneth Holt talk with Dr. Kelsea Best, a post-doctoral researcher in Civil and Environmental Engineering at the University of Maryland.

01:10 An overview of her research on environmental migration in Bangladesh.

02:30 A description of her agent-based modeling tool and its utility in her research.

An overview of agent-based modeling: https://en.wikipedia.org/wiki/Agent-based_model 

04:50 What was the academic path that led to this focus? (from chemical engineering to addressing climate justice through data analysis)

07:20 Out of 2,000 variables in your dataset, how did Machine Learning help you gain insight?

An overview of machine learning: https://en.wikipedia.org/wiki/Machine_learning 

09:50 Did anything surprise you in your analysis?

12:05 Is the enormous dataset you're describing publicly available? (Not yet. But the Adams dataset, similarly valuable and also about Bangladesh, is available.) 

The Adams dataset from Bangladesh - https://reshare.ukdataservice.ac.uk/852356/

13:30 Discussing why people do or do not want to migrate, and the many pressures around either choice. 

16:00 Developing a board game to explore migration decisions, and the scientific creativity appearing as we try to understand these complex issues. 

16:30 Discovering the importance of migration narratives, and deciding to collect and incorporate migration stories to enrich the meaning of survey data. 

StoryMap with Bangladeshi migrant stories- https://storymaps.arcgis.com/stories/fd168c7804ae489b99c7311a4c805b31

21:15 Where can our listeners take a close look at your agent-based modeling code?

Dr. Best's agent-based model code- https://zenodo.org/record/4526330#.Y7cNMXbMKUc

22:35 The WWHGD Human Geography Library resources on environmental migration. 

WWHGD.org 

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Opinions expressed on this podcast do not necessarily reflect the views of the WWHGD sponsors and should not be construed as an endorsement.

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