The concept of anomalous clustering applies to finding individual clusters on a digital geography map supplied with a single feature such as brightness or temperature. An algorithm derived within the individual anomalous cluster framework extends the so-called region growing algorithms. Yet our approach differs in that the algorithm parameter values are not expert-driven but rather derived from the anomalous clustering model. This novel framework successfully applies to the issue of automatically delineating coastal upwelling from Sea Surface Temperature (SST) maps, a natural phenomenon seasonally occurring in coastal waters.
CITATION STYLE
Nascimento, S., & Mirkin, B. (2017). Applying anomalous cluster approach to spatial clustering. Studies in Computational Intelligence, 683, 147–157. https://doi.org/10.1007/978-3-319-51052-1_10
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