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 language | English (US) |
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Title of host publication | Space-Time Integration in Geography and GIScience |
Subtitle of host publication | Research Frontiers in the US and China |
Publisher | Springer Netherlands |
Pages | 301-326 |
Number of pages | 26 |
ISBN (Electronic) | 9789401792059 |
ISBN (Print) | 9789401792042 |
DOIs | |
State | Published - Jan 1 2015 |
Bibliographical note
Publisher Copyright:© Springer Science+Business Media Dordrecht 2015.