In May 2018, UCGIS and the Cartography and Geographic Information Society (CaGIS) co-hosted a Symposium & AutoCarto in Madison, Wisconsin, at the historic Concourse Hotel in downtown Madison, Wisconsin. The theme, Frontiers of Geospatial Data Science, allowed us to focus our discussions and paper presentations around topics of big data, deep learning, data-intensive computing platforms, and visualization, as well as geospatial big data sources and applications such as location-aware social media and autonomous vehicles. We considered connections between Geospatial Science and the burgeoning field of Data Science, seen in newly named academic departments and calls for funded research. Participants contributed their ideas for what next steps UCGIS might take with a Data Science initiative, and we have now released a UCGIS Statement on Data Science (pdf) in response. 

The full printed proceedings (pdf) from the event are available, as well as many of the paper and poster presentations themselves. The two students selected by the conference attendees for Scholarship Awards for their posters are Yanghui Kang (University of Wisconsin - Madison) for Predicting County-Level Maize Yield with Deep Learning and Satellite Data, and Samuel Levin (University of Texas - Dallas), for Viewshed Analysis for UAS Flight Planning.  

 Symposium Discussion Yanghui Kang Forecasting Maize Yield UW Campus Field Trip  Samuel Levin Viewshed Analysis for UAS Flight Planning UCGIS 2018 Award Winners Albrecht, Couclelis, Clarke Reception and Poster Session

 

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What's happening with the Geospatial Data Act? 

Whatever happened to the bipartisan Geospatial Data Act (GDA) of 2017, you may be wondering? This important bill is designed to facilitate and support geospatial data development, sharing, and coordination across federal agencies and partnerships with state and local governments, towards a more robust National Spatial Data Infrastructure (NSDI). Unfortunately, the bill has yet to reach congressional floors for a vote. Read more at our blog.