Modeling flood zones on the basis of time series forecasting and GIS-technologies by the example of the Republic of Bashkortostan
Автор: Palchevsky E.V., Antonov V.V., Rodionova L.E., Kromina L.A., Fakhrullina A.R.
Журнал: Компьютерная оптика @computer-optics
Рубрика: Обработка изображений, распознавание образов
Статья в выпуске: 6 т.48, 2024 года.
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A specialized GIS Web is proposed, implemented by integrating an artificial neural network and geotechnologies and providing early forecasting and modeling of flood zones up to five days in advance. The methods and algorithms implemented within this GIS Web allow daily forecasting of time series based on retrospective data on water levels and total water inflow, air and water temperature, snow cover thickness and precipitation, wind speed and atmospheric pressure. At the same time, the possibility of early modeling and visualization of river floods is realized only on the basis of the obtained predictive values of the water level. This will enable specialized organizations and services, as well as management bodies to make decisions related to flood control measures in advance and as soon as possible.
Geographic information system, flood zone modelling, time series forecasting, artificial neural networks
Короткий адрес: https://sciup.org/140310418
IDR: 140310418 | DOI: 10.18287/2412-6179-CO-1418