Mapping Heterogeneous Urban Landscapes from the Fusion of Digital Surface Model and Unmanned Aerial Vehicle-Based Images Using Adaptive Multiscale Image Segmentation and Classification

Considering the high-level details in an ultrahigh-spatial-resolution (UHSR) unmanned aerial vehicle (UAV) dataset, detailed mapping of heterogeneous urban landscapes is extremely challenging because of the spectral similarity between classes. In this study, adaptive hierarchical image segmentation...

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Autors principals:	Mohamed Barakat A. Gibril, Bahareh Kalantar, Rami Al-Ruzouq, Naonori Ueda, Vahideh Saeidi, Abdallah Shanableh, Shattri Mansor, Helmi Z. M. Shafri
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2020-03-01
Col·lecció:	Remote Sensing
Matèries:	unmanned aerial vehicle urban LULC GEOBIA multiscale classification
Accés en línia:	https://www.mdpi.com/2072-4292/12/7/1081
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