Supervised Spatial Regionalization using the Karhunen-Loève Expansion and Minimum Spanning Trees

Journal of Data Science

article

Ranadeep Daw¹  Christopher K. Wikle¹ 

[1] Department of Statistics, University of Missouri

关键词: connectivity graph;    ecological fallacy;    Karhunen-Loève expansion;    minimum spanning tree;    regionalization;    spatial data;   

DOI  :  10.6339/22-JDS1077

学科分类：土木及结构工程学

来源: JDS

【 摘 要 】

The article presents a methodology for supervised regionalization of data on a spatial domain. Defining a spatial process at multiple scales leads to the famous ecological fallacy problem. Here, we use the ecological fallacy as the basis for a minimization criterion to obtain the intended regions. The Karhunen-Loève Expansion of the spatial process maintains the relationship between the realizations from multiple resolutions. Specifically, we use the Karhunen-Loève Expansion to define the regionalization error so that the ecological fallacy is minimized. The contiguous regionalization is done using the minimum spanning tree formed from the spatial locations and the data. Then, regionalization becomes similar to pruning edges from the minimum spanning tree. The methodology is demonstrated using simulated and real data examples.

【 授权许可】

CC BY