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ESIP Winter Meeting 2013 Geospatial Breakout Session. Tommy Jasmin, Adam Estrada, Paul Ramirez, Cameron Goodale 8 Jan 2013 University of Wisconsin Space Science and Engineering Center. 2012 – First Six Months. Hyrax 1.8 and OPeNDAP - James Gallagher
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ESIP Winter Meeting 2013Geospatial Breakout Session Tommy Jasmin, Adam Estrada, Paul Ramirez, Cameron Goodale 8 Jan 2013 University of Wisconsin Space Science and Engineering Center
2012 – First Six Months • Hyrax 1.8 and OPeNDAP • - James Gallagher • ESRI GeoScience Data Workshop • - Paul Ramirez • Python-based GIS technologies • - Cameron Goodale • GDAL and complex datasets • - Frank Warmerdam • GIS in disaster response, ncISO metadata discovery • - Dave Neufeld • GeoCloud – deploying FGS in the Cloud • - Doug Nebert
Summer Meeting - Intro • Exponential growth in GIS data volume • Changing nature of metadata • Importance of interoperability • Spatial Data Infrastructures (SDIs) • Endless variety of useful applications
Summer Meeting - ARML Augmented Reality Markup Language - by Manil Maskey
Summer Meeting - WorldView EOSDIS Global Imagery Browse Services - by Ryan Boller
Summer Meeting – JPL Snow Data System GeoDatabase of MODIS-derived products - by Paul Ramirez
Summer Meeting - CMDS Coastal Marine Discovery Service - by Ed Armstrong
Atmospheric Imagery in GIS SSEC WMS, near real-time, GIS overlay - by Sam Batzli
RAMADDA – CMS for Earth Science data Repository, Publishing, Collaboration - by Jeff McWhirter
Our Focus Today ESIP Winter Meeting 2013 ESIP Advancing Earth Science Information From Climate Assessment, To Intelligence, To Action
Geospatial Grand Challenges Poverty, Disease, Food and Water Natural Disasters Environmental Sustainability Education
Geography of Human Poverty www.worldmapper.org
Natural Disasters 1975-2011 www.emdat.be
Natural Disaster Costs 1975-2011 www.emdat.be
Natural Disaster Deaths 1975-2011 www.emdat.be
Velocity of Climate Change Loarie, et al: Nature, 2009
Mashups – Wolf habitat in WI Linear regression model Dependent variable: wolf pack ranges Independent variables: human population, prey density, roads, land cover type, land ownership, and more Wide variety of geospatial data types, sources, and formats used
Mashups – Wolf habitat in WI What was the biggest factor?