Особенности дешифрирования урбанизированных территорий северных городов по спутниковым снимкам landsat на примере г. Якутск

• Main Authors: Zakharov, Moisei, Danilov, Yuri, GADAL, Sébastien
• Other Authors: North-Eastern Federal University, Études des Structures, des Processus d’Adaptation et des Changements de l’Espace (ESPACE), Université Côte d'Azur (UCA)-Avignon Université (AU)-Université Nice Sophia Antipolis (. - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Aix Marseille Université (AMU), ANR-15-CE22-0006,PUR,Pôles URbains(2015)
• Format: Article in Journal/Newspaper
• Language: Russian
• Published: HAL CCSD 2019
• Subjects: Cartography; Urban monitoring; VIBI index; Urban territories; Northern cities; Yakutsk; Russia; Remote sensing; Landsat 8 OLI; картография; мониторинг; урбанизированные территории; geo; envir; Якутск
• Online Access: https://hal.archives-ouvertes.fr/hal-02471730

International audience Currently, there are many approaches to the recognition of urbanized areas, mainly based on the methods supervised and unsupervised spectral image classifications. D. Statakis, K. Perakis, I. Yu. Savin proposed an index (VIBI - Vegetation Index - Built up Index), which is a combination of widely known NDVI and NDBI. In this article, we will conduct the experience of deciphering the urbanized territories of Yakutsk based on the VIBI index approach and define the features of the use for northern cities. The purpose of the study is to determine the most effective method for the urbanized territories of northern cities using the example of Yakutsk. We applied the VIBI index on Landsat 8 OLI multi-temporal for the recognition of the urban structures of Yakutsk. Images selected are from June 26, 2017, and November 4, 2017. Winter images are more efficient due to the absence of open water surfaces and various types of open soils. Results of the VIBI index are combined in GIS with other urban databases for the identification of the datchas and year-round houses.