Conference Paper

Analyzing change in spatial data by utilizing polygon models

DOI: 10.1145/1823854.1823880 Conference: Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application, COM.Geo 2010, Washington, DC, USA, June 21-23, 2010
Source: DBLP


Analyzing change in spatial data is critical for many applications including developing early warning systems that monitor environmental conditions, epidemiology, crime monitoring, and automatic surveillance. In this paper, we present a framework for the detection and analysis of patterns of change; the framework analyzes change by comparing sets of polygons. A contour clustering algorithm is utilized to obtain polygon models from spatial datasets. A set of change predicates is introduced to analyze changes between different models which capture various types of changes, such as novel concepts, concept drift, and concept disappearance. We evaluate our framework in case studies that center on ozone pollution monitoring, and on diagnosing glaucoma from visual field analysis.

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