Endmember representation of human geography layers


This paper presents an endmember estimation and representation approach for human geography data cubes. Human-related factors that can be mapped for a geographic region include factors relating to population, age, religion, education, medical access and others. Given these hundreds (or even thousands) of factors mapped over a region, it is extremely difficult for an analyst to summarize and understand the interactions between all of these factors. In this paper, a method to provide a compact representation and visualization of hundreds of human geography layers is presented. These are large data cubes containing a range of human geographic information including some represented using fuzzy values. Results on a human geography data cube compiled for the state of Missouri, USA is presented.




A. Buck, A. Zare, J. Keller, and M. Popescu, “Endmember representation of human geography layers,” in IEEE Symp. Computational Intelligence in Big Data (CIBD), 2014. 
Title = {Endmember representation of human geography layers},
Author = {Andrew Buck and Alina Zare and James Keller and Mihail Popescu},
Booktitle = {IEEE Symp. Computational Intelligence in Big Data (CIBD)},
Year = {2014},
Month = {Dec.},
Doi = {10.1109/CIBD.2014.7011520},