Generation of Zonal Map From Point Data via Weighted Skeletonization by Influence Zone

Abstract

Data about many variables are available as numerical values at specific geographical locations. We develop a methodology based on mathematical morphology to convert point-specific data into zonal map. This methodology relies on weighted skeletonization by zone of influence that determines the points of contact of multiple frontlines propagating, from various points spread over the space, at the traveling rates depending upon the variable's strength. We demonstrate this approach for converting rainfall data available at specific rain gauge locations (points) into a spatially distributed zonal map that suggests zones of equal rainfall.