Social and Behavioral Sciences Commons^™

Characterizing Clustering Models Of High-Dimensional Remotely Sensed Data Using Subsampled Field-Subfield Spatial Cross-Validated Random Forests, Andrew B. Whetten

International Journal of Geospatial and Environmental Research

Clustering models are regularly used to construct meaningful groups of observations within complex datasets, and they are an exceptional tool for spatial exploratory analysis. The clusters detected in a recent spatio-temporal cluster analysis of leaf area index (LAI) in the Columbia River Basin (CRB) require further investigation since they are only derived using a single greenness metric. It is of great interest to further understand how greening indices can be used to determine separation of sites across an array of remotely sensed environmental attributes. In this prior work, there are highly localized minority clusters that were detected to be most …