Multi-Level Morphometric Characterization of Built-up Areas and Change Detection in Siberian Sub-Arctic Urban Area: Yakutsk

• Published in: ISPRS International Journal of Geo-Information
• Main Authors: Gadal, Sébastien, Ouerghemmi, Walid
• Other Authors: 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)-Avignon Université (AU)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA), ANR-15-CE22-0006,PUR,Pôles URbains(2015), ANR-10-EQPX-0020,GEOSUD,GEOSUD : Infrastructure nationale d'imagerie satellitaire pour la recherche sur l'environnement et les territoires et ses applications à la gestion et aux politiques publiques(2010)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2019
• Subjects: Built-ups structures; Geometric attributes morphometric rules; Object recognition; Architecture and urbanism; Multiband imagery; Image analysis; Yakutsk; Russia; Arctic; Urban sprawl; Socioeconomic functions; [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]; [SHS.STAT]Humanities and Social Sciences/Methods and statistics; [SDE.ES]Environmental Sciences/Environment and Society; [SHS.GEO]Humanities and Social Sciences/Geography; [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
• Online Access: https://hal.science/hal-02056619; https://hal.science/hal-02056619/document; https://hal.science/hal-02056619/file/ijgi-08-00129.pdf; https://doi.org/10.3390/ijgi8030129

International audience Recognition and characterization of built-up areas in the Siberian sub-Arctic urban territories of Yakutsk are dependent on two main factors: (1) the season (snow and ice from October to the end of April, the flooding period in May, and the summertime), which influences the accuracy of urban object detection, and (2) the urban structure, which influences the morphological recognition and characterization of built-up areas. In this study, high repetitiveness remote sensing Sentinel-2A and SPOT 6 high-resolution satellite images were combined to characterize and detect urban built-up areas over the city of Yakutsk. High temporal resolution of Sentinel-2A allows land use change detection and metric spatial resolution of SPOT 6 allows the characterization of built-up areas' socioeconomic functions and uses.