Ryan Engstrom - Director of the Data Science Program, Department of Geography, George Washington University

In this episode of “Through the Human Geography Lens”, hosts Terri Ryan and Eric Rasmussen sit down with Ryan Engstrom, Director of the Data Science Program within the Department of Geography at George Washington University.

00:50 Professor Engstrom’s research interests

01:35 Defining “deprived areas”

Kuffer, Thomson, D. R., Boo, G., Mahabir, R., Grippa, T., Vanhuysse, S., Engstrom, R., Ndugwa, R., Makau, J., Darin, E., de Albuquerque, J. P., & Kabaria, C. (2020). The Role of Earth Observation in an Integrated Deprived Area Mapping “System” for Low-to-Middle Income Countries. Remote Sensing (Basel, Switzerland), 12(6), 982–. https://doi.org/10.3390/rs12060982

02:32  Insights from work in Accra, Ghana

03:40  “Do the most vulnerable people live in the worst slums?”

05:30  Using geospatial data to assess the population/environment balance

06:45  Working with census takers.

08:00  Working in the Arctic, particularly in Russia, and the value of open Census data

09:05  Validating data: survey and satellite integration

10:12  Assessing spatial distribution by economic class: surveys often miss the wealthy

12:00  Youth Mappers (open sourced at OpenStreetMap, 300+ chapters, funded by USAID)

https://www.youthmappers.org/

15:10  Geography 2050 for elementary and high school support.

https://www.geography2050.org/

15:45  Geospatial tools in use at the university level

17:02  Open-source data models, not just the data: GitHub availability (and it’s working well)

https://github.com/topics/geospatial-analytics

18:35  Major data sources and managers that have appeared over the past few years

https://github.com/sacridini/Awesome-Geospatial

https://www.openstreetmap.org/#map=4/38.01/-95.84

https://earthengine.google.com/

https://aws.amazon.com/?nc2=h_lg

19:25 Example: OSM mapping enhancements in Accra

https://www.openstreetmap.org/node/27565080#map=9/5.3070/0.4971

20:04  Using machine learning for co-variate income analysis in Belize

Hersh, Engstrom, R., & Mann, M. (2021). Open data for algorithms: mapping poverty in Belize using open satellite derived features and machine learning. Information Technology for Development, 27(2), 263–292. 

https://doi.org/10.1080/02681102.2020.1811945

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