Application of machine learning to satellite data for classification of the precipitation spatial characteristics – Mariia Kavalerova
Mariia Kavalerova
Master's thesis
Application of machine learning to satellite data for classification of the precipitation spatial characteristics
Abstract:
Precipitation analysis of the trends and changes are taking part in climate change understanding. In addition, it plays a vital role in predicting and investigating extreme weather events, such as floods and droughts. Extreme events threaten climate-sensitive economic sectors, including agriculture, forestry, energy, insurance and others. In precipitation analysis, temporal changes and spatial variability …more
Language used: English
Date on which the thesis was submitted / produced: 31. 3. 2022
Thesis defence
- Supervisor: doc. Mgr. Ing. Ioannis Markonis, Ph.D.
Citation record
ISO 690-compliant citation record:
KAVALEROVA, Mariia. \textit{Application of machine learning to satellite data for classification of the precipitation spatial characteristics}. Online. Master's thesis. Praha: Czech University of Life Sciences Prague, Faculty of Environmental Sciences. 2022. Available from: https://theses.cz/id/zksyti/.
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Institution archiving the thesis and making it accessible: Česká zemědělská univerzita v Praze, Fakulta životního prostředíCzech University of Life Sciences Prague
Faculty of Environmental SciencesMaster programme / field:
Landscape Engineering / Environmental Modelling
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