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2 décembre 2021
- handle: 10670/1.lthcr6
- hal: hal-03502208
http://creativecommons.org/licenses/by-nc/
Mots-clés
Metropolisation Adaptation Simulation Urban change modelling Global warming Multi-level analysis Extreme environment Remote Sensing Machine learning Deep learning Yakutsk Arctic RussiaSujets proches
Global warming--Environmental aspects Warming, Global Natural science Sciences Science of science Nurture and nature Nature versus nurture Genetics and environment Nature--Nurture Environment Heredity and environment Modelmaking Modelling Model-making Molding (Clay, plaster, etc.) Clay modeling Modelling Learning, Machine Learning process Environment Ecological science Environmental biology Bionomics Ecological sciences Environment Balance of nature Oecology Biology--Ecology Ecological processes Arctic Ocean Region Arctic, The Far North Arctic The Arctic Environment Scholarship LearningCiter ce document
Sébastien Gadal et al., « Spatial modelling of the Arctic metapolis: Yakutsk », HAL-SHS : géographie, ID : 10670/1.lthcr6
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Résumé
The process of metropolisation of Yakutsk is one of the most unique geographic phenomena. Since the end of the Soviet Union, the city of 193000 inhabitants growing fastly to cross in 2021 up to 33000 people covering today almost 1 million square kilometres in the extreme Arctic environment and climate. The population of the Yakutsk metropolis developed strategies of adaptation we are going to analyse. Scenarios of possible transformations of the metropolis including the impacts of global warming have been developed at different scales and temporalities (Landsat Series, Sentinel 2, DMSP, and VIIRS) based on machine learning and deep learning processing.