A phenomenon is defined as any state or process known through the senses rather than by intuition or reasoning, and thus is an observable event, especially something special or unusual. A geophysical phenomenon in the context of geoscience data can be characterized as a spatial region which is significantly different from the rest of the image; having higher/lower than average background intensity value; and having higher variation in intensity when compared to the remaining data points. This paper will describe two variations of the Phenomena Extraction Algorithm (PEA). The PEA consists of three components: a hierarchical splitting to efficiently decompose geoscience data into smaller regions; a set of statistical tests to determine whether decomposed region meets the definition of a geophysical phenomenon and an optimization algorithm to determine the best thresholds needed by these statistical tests. The two variations of the algorithm were tested on a synthetic dataset in a series of experiments. The results from these experiments will be presented in this paper. The use of PEA in a proof-of-concept effort within Linked Environment for Atmospheric Discovery (LEAD), a large NSF funded Information Technology Research project, will also be described.
['Rahul Ramachandran', 'Xiang Li', 'Srinivas Mowa', 'Sara J. Graves']
A Simple and Efficient Feature Extraction Algorithm for Geophysical Phenomena