Multiscale and multi-temporal modelling of urban change structures in the Subarctic East Siberian metropolis of Yakutsk
- Others:
- Aix-Marseille Université - Faculté des Arts, Lettres, Langues et Sciences Humaines (AMU ALLSH) ; Aix Marseille Université (AMU)
- Études des Structures, des Processus d'Adaptation et des Changements de l'Espace (ESPACE) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- North-Eastern Federal University
- Kaunas University of Technology (KTU)
- Hassan II Institute of Agronomy and Veterinary, Department of Geodesy and Topography, Geomatics Science and Engineering, Morocco
- University of Lodz
- Cracow University of Technology,
- Lodz University of Technology
- FMSH-RBSF OSAMA (development Of an optimal human Security Model for The Arctic)
- CNES THEIA TOSCA AIMCEE (Apport de l'Imagerie satellitaire Multi-Capteurs pour répondre aux Enjeux Environnementaux et sociétaux des socio-systèmes urbains)
- ANR-15-CE22-0006,PUR,Pôles URbains(2015)
Citation
Description
In the last twenty years, the Metropolis of Yakutsk has experienced significant changes characterised by intense urban growth, densification, and urban structure changes in a complex geographical environment: extremely low temperature during six to seven months, impacts of permafrost dynamics and relative melting, seasonal exposure to ice breakup on the suburban areas. The urban structure and land-use changes conditioned by the urban growth and environmental impacts are analysed at two geographic scales: the meso-urban level with the use of the Landsat-5 TM, Landsat-8 OLI, and Sentinel-2 MSI satellites images covering the period from 2010 to 2020; and at the regional level with the DMSP-OLS PL (1995-2013) and VIIRS-DNB (2015-2020) sensors. The recognition of the urban structures and land use transformations at both scales are based on the use of combined machine learning data processing. The simulations of the urban structures and land use evolutions to 2030 at the meso-urban and regional scales by Markov chain cellular automata give comparable results of the future trends of the Yakutsk metropolis: reduction of vegetation, forests areas (due to forest fires) and agriculture zones; the increase of bare soil, water surfaces and new urban areas.
Abstract
International audience
Additional details
- URL
- https://hal.archives-ouvertes.fr/hal-03787176
- URN
- urn:oai:HAL:hal-03787176v1
- Origin repository
- UNICA