research-article

Analyzing change in spatial data by utilizing polygon models

Authors:

Vadeerat Rinsurongkawong,

Chun Sheng Chen,

Christoph F. Eick,

Michael D. TwaAuthors Info & Claims

COM.Geo '10: Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application

Article No.: 22, Pages 1 - 8

https://doi.org/10.1145/1823854.1823880

Published: 21 June 2010 Publication History

Abstract

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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Cited By

Wang SEick C(2017)A data mining framework for environmental and geo-spatial data analysisInternational Journal of Data Science and Analytics10.1007/s41060-017-0075-95:2-3(83-98)Online publication date: 30-Sep-2017
https://doi.org/10.1007/s41060-017-0075-9
Wang SChen CRinsurongkawong VAkdag FEick CLin JCervone GWaters N(2010)A polygon-based methodology for mining related spatial datasetsProceedings of the 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics10.1145/1869890.1869891(1-8)Online publication date: 2-Nov-2010
https://dl.acm.org/doi/10.1145/1869890.1869891

Index Terms

Analyzing change in spatial data by utilizing polygon models

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cover image ACM Other conferences

COM.Geo '10: Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application

June 2010

274 pages

ISBN:9781450300315

DOI:10.1145/1823854

General Chair:
Lindi Liao

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 June 2010

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COM.Geo '10

COM.Geo '10: 1st International Conference on Computing for Geospatial Research and Application

June 21 - 23, 2010

Washington, D.C., USA

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Cited By

Wang SEick C(2017)A data mining framework for environmental and geo-spatial data analysisInternational Journal of Data Science and Analytics10.1007/s41060-017-0075-95:2-3(83-98)Online publication date: 30-Sep-2017
https://doi.org/10.1007/s41060-017-0075-9
Wang SChen CRinsurongkawong VAkdag FEick CLin JCervone GWaters N(2010)A polygon-based methodology for mining related spatial datasetsProceedings of the 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics10.1145/1869890.1869891(1-8)Online publication date: 2-Nov-2010
https://dl.acm.org/doi/10.1145/1869890.1869891

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