Seminar: “A Map-ematical Framework for Quantitative Analysis of Mapped Data: Map Analysis and GIS Modeling for Understanding and Communicating Spatial Patterns and Relationships within STEM Discipline Contexts”
February 20, 2015
Noon – 1:00pm (with informal discussion to follow)
2150 E Evans Ave, University of Denver, Denver, CO
Anderson Academic Commons, Room 152
Denver, CO – Joe Berry, Adjunct Faculty in Geosciences at the University, Adjunct Faculty in Natural Resources at Colorado State University, and Principal, Berry and Associates // Spatial Information Systems presented a Brown Bag seminar on “A Map-ematical Framework for Quantitative Analysis of Mapped Data: Map Analysis and GIS Modeling for Understanding and Communicating Spatial Patterns and Relationships within STEM Discipline Contexts.”
The event was sponsored by the Center for Statistics and Visualization and the Department of Geography & the Environment. All of the supporting materials including the Handout with links to online references and the PowerPoint with instructor notes are available online at www.innovativegis.com/basis/Present/Mapematics_2015/.
This presentation described a comprehensive framework for map analysis and modeling concepts and procedures as direct spatial extensions of traditional mathematics and statistics, enabling individuals with minimal or no GIS background to develop spatial reasoning and problem solving skills—thinking with maps.
The intent of the presentation was 1) to get the Geospatial community to look beyond its traditional mapping and geoquery roles and 2) to engage the STEM disciplines in the validity of quantitative analysis of spatial data. The thesis is that there is common ground in the recognition that “maps are numbers first, pictures later” and that the spatial distribution of these numbers is as important as their numerical distribution in explaining relationships among variables, be they scalar or mapped. The presentation described the direct extension of traditional math/stat procedures into the spatial realm thereby infusing understanding and communication of spatial patterns into quantitative data analysis.