Spatiotemporal Data Mining: A Survey
It offers a comprehensive resource for researchers and practitioners in fields like public safety and ecology, but it is incremental as it builds on existing surveys.
This paper provides an updated survey of spatiotemporal data mining methods, addressing the need for current reviews and including a detailed survey of parallel techniques for handling big spatial and spatiotemporal data.
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data. They are used in various application domains such as public safety, ecology, epidemiology, earth science, etc. This problem is challenging because of the high societal cost of spurious patterns and exorbitant computational cost. Recent surveys of spatiotemporal data mining need update due to rapid growth. In addition, they did not adequately survey parallel techniques for spatiotemporal data mining. This paper provides a more up-to-date survey of spatiotemporal data mining methods. Furthermore, it has a detailed survey of parallel formulations of spatiotemporal data mining.