Project Title:
Scalable Geospatial Computing
This research is situated at the intersection of computational science and geographic information science. The research data includes climate and agricultural data and various geospatial data. This collaborative work has two aims. The first is to analyze spatial data searching for patterns and anomalies to improve understanding in various scientific areas. The second is to improve the scalability and performance of several codes including the design and development of a domain-specific programming language.
Project Investigators
Annaliese Ackerman
Mohsen Ahmadkhani
Matthew Braaksma
Laure Briol
Jaret Cleveland
Owen Connolly
Alexander Danielson
Isabel Eguizabal
Lucas Flom
Logan Gall
Ryan Gavin
Eric Gibson
Jacob Harris
Arlan Hegenbarth
Jasper Johnson
Miles Jungclaus
Jacob Kastenbauer
Gregory Kohler
Easton Koudelka
Zachary Krause
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