Mapping heterogeneous urban landscapes from the fusion of digital surface model and unmanned aerial vehicle-based images using adaptive multiscale image segmentation and classification

• Main Authors: Gibril, Mohamed Barakat A., Kalantar, Bahareh, Al-Ruzouq, Rami, Ueda, Naonori, Saeidi, Vahideh, Shanableh, Abdallah, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi
• Format: Article
• Language: English
• Published: MDPI 2020
• Online Access: http://psasir.upm.edu.my/id/eprint/38105/1/38105.pdf; http://psasir.upm.edu.my/id/eprint/38105/; https://www.mdpi.com/2072-4292/12/7/1081
• Institution: Universiti Putra Malaysia

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...