Spatiotemporal change pattern mining: A multi-disciplinary perspective

Xun Zhou, Shashi Shekhar, Pradeep Mohan

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

Given a definition of change and a dataset about a spatiotemporal (ST) phenomenon, ST change pattern mining is the process of identifying the location and/or time frame of shifts in phenomenon. Detecting patterns of change over space and/or time is an increasingly important activity in application domains ranging from climate science to public health. Researchers have developed numerous techniques to facilitate themining of such patterns. Addressing domain specific challenges, they have often worked in distinct research settings, most notably time series analysis, remote sensing, and spatial statistics. Although they tend to target different aspects of the change pattern mining problem, there is much researchers could learn from one another to advance their respective areas.

Original languageEnglish (US)
Title of host publicationSpace-Time Integration in Geography and GIScience
Subtitle of host publicationResearch Frontiers in the US and China
PublisherSpringer Netherlands
Pages301-326
Number of pages26
ISBN (Electronic)9789401792059
ISBN (Print)9789401792042
DOIs
StatePublished - Jan 1 2015

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    Zhou, X., Shekhar, S., & Mohan, P. (2015). Spatiotemporal change pattern mining: A multi-disciplinary perspective. In Space-Time Integration in Geography and GIScience: Research Frontiers in the US and China (pp. 301-326). Springer Netherlands. https://doi.org/10.1007/978-94-017-9205-9_17