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Publication Information

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Title: Improved analyses using function datasets and statistical modeling

Author: Hogland, John S.; Anderson, Nathaniel M.;

Date: 2014

Source: In: Proceedings of the 2014 ESRI Users Conference; July 14-18, 2014, San Diego, CA. Redlands, CA: Environmental Systems Research Institute. Online: http://proceedings.esri.com/library/userconf/proc14/papers/166_182.pdf.

Publication Series: Paper (invited, offered, keynote)

Description: Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space and have limited statistical functionality and machine learning algorithms. To address this issue, we developed a new modeling framework using C# and ArcObjects and integrated that framework with .Net numeric libraries. Our new framework streamlines raster modeling and facilitates predictive modeling and statistical inference.

Keywords: modeling, spatial analysis, geographic information system (GIS)

Publication Notes:

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Citation:


Hogland, John S.; Anderson, Nathaniel M. 2014. Improved analyses using function datasets and statistical modeling. In: Proceedings of the 2014 ESRI Users Conference; July 14-18, 2014, San Diego, CA. Redlands, CA: Environmental Systems Research Institute. Online: http://proceedings.esri.com/library/userconf/proc14/papers/166_182.pdf.

 


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