Decision tree classification model for detecting and tracking precipitating objects from series of meteorological images
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...
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| Tác giả chính: | |
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| Định dạng: | BB |
| Ngôn ngữ: | eng |
| Thông tin xuất bản: |
2020
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| Chủ đề: | |
| Truy cập trực tuyến: | http://tailieuso.tlu.edu.vn/handle/DHTL/4572 |
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| Tóm tắt: | 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. |
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