Change Detection in Meteorological Data
نویسندگان
چکیده
Change detection is an important task in signal analysis, data mining, and image processing. In meteorology research, change is frequently associated with severe weather events or climate anomalies. Detecting change is crucial for weather and climate analysis. In this paper, we propose a wavelet based approach to analyze short term changes in the global meteorological data. We design a suite of algorithms to effectively detect the changes considering both spatial and temporal perspectives. The algorithms were implemented and evaluated with a real-world meteorological data set.
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