Controlling patterns of geospatial phenomena |
| |
Authors: | Tomasz F Stepinski Wei Ding Christoph F Eick |
| |
Affiliation: | (1) Lunar and Planetary Institute, Houston, TX 77058, USA;(2) Department of Computer Science, University of Massachusetts Boston, Boston, MA 02125-3393, USA;(3) Department of Computer Science, University of Houston, Houston, TX 77204-3010, USA |
| |
Abstract: | Modeling spatially distributed phenomena in terms of its controlling factors is a recurring problem in geoscience. Most efforts
concentrate on predicting the value of response variable in terms of controlling variables either through a physical model
or a regression model. However, many geospatial systems comprises complex, nonlinear, and spatially non-uniform relationships,
making it difficult to even formulate a viable model. This paper focuses on spatial partitioning of controlling variables
that are attributed to a particular range of a response variable. Thus, the presented method surveys spatially distributed
relationships between predictors and response. The method is based on association analysis technique of identifying emerging
patterns, which are extended in order to be applied more effectively to geospatial data sets. The outcome of the method is
a list of spatial footprints, each characterized by a unique “controlling pattern”—a list of specific values of predictors
that locally correlate with a specified value of response variable. Mapping the controlling footprints reveals geographic
regionalization of relationship between predictors and response. The data mining underpinnings of the method are given and
its application to a real world problem is demonstrated using an expository example focusing on determining variety of environmental
associations of high vegetation density across the continental United States. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|