Abstract

Improved analyses using Function Datasets and statistical modeling
Track: Modeling Techniques
Authors: John Hogland, Nathaniel Anderson

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 types of statistical 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 to streamline the raster modeling process and facilitate predictive modeling and statistical inferences.