Decision tree classification model for detecting and tracking precipitating objects from series of meteorological images

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Ramirez, S. and Lizarazo, I. (2016) Decision tree classification model for detecting and tracking precipitating objects from series of meteorological images. In: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) .

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Event: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC)
Abstract:Accurate detection and identification of convective (cumulonimbus) clouds, which are potentially precipitating objects, as well as tracking cloud movement, are important tasks to locate and predict precipitation. In the present work, a Decision Tree classification model was used to locate and track precipitating objects from series of GOES-13 meteorological image sub-scenes covering the territory of Colombia, located to the northwest corner of South America. Results show that it is possible to infer a classification model that can be used repeatedly for accurately locating and tracking precipitating objects from multispectral meteorological images.
Item Type:Conference or Workshop Item (Paper)
Link to this item:https://doi.org/10.3990/2.384
Conference URL:https://www.geobia2016.com/
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