WE3.P4.3
Identification of Roof Materials in Urban Hot Spots from Remote Sensing Imagery Using Deep Learning Methods
Qingyu Li, The Chinese University of Hong Kong, Shenzhen, China; Xinyue Yang, Technical University of Munich, Germany
Session:
WE3.P4: Remote Sensing and Deep Learning for Urban Climate, Energy, and Environmental Insights Oral
Track:
Land Applications
Location:
Room P4
Presentation Time:
Wednesday, 6 August, 13:45 - 14:00
Session Co-Chairs:
Yifang Ban, KTH Royal Institute of Technology and Claudio Persello, University of Twente
Presentation
Discussion
Resources
No resources available.
Session WE3.P4
WE3.P4.1: Multi-Scale and Coordinate Attention-Based CNN for Local Climate Zone Classification
Ximing Liu, Luigi Russo, Wenbo Li, Paolo Gamba, University of Pavia, Italy; Alim Samat, Xinjiang Institute of Ecology and Geography, China; Silvia Liberata Ullo, University of Sannio, Italy
WE3.P4.2: EXPLORING THE SPATIOTEMPORAL EVOLUTION PATTERNS OF URBAN HEAT ISLAND WITH A NETWORK-BASED APPROACH
Kang Zou, Xinyu Yu, Man Sing Wong, Kai Qin, Rui Zhu, Songyang Li, The Hong Kong Polytechnic University, China
WE3.P4.3: Identification of Roof Materials in Urban Hot Spots from Remote Sensing Imagery Using Deep Learning Methods
Qingyu Li, The Chinese University of Hong Kong, Shenzhen, China; Xinyue Yang, Technical University of Munich, Germany
WE3.P4.4: Multi-Scenario analysis of rooftop greening regulation on runoff effects based on adaptive Evaluation: A case study of Macau, China
Yixuan Wang, Tianjin University, China; Jiayu Wang, Beijing University of Civil Engineering and Architecture, China; Tian Chen, Tianjin University, China
WE3.P4.5: DEEP LEARNING-ENABLED ASSESSMENT OF ROOFTOP SOLAR POTENTIAL: INSIGHTS FOR SUSTAINABLE URBAN ENERGY PLANNING IN PAKISTAN
Muhammad Kamran Lodhi, Yumin Tan, Xiaolu Wang, Agus Suprijanto, Lukman Alage ISIAKA, Beihang University, China
Resources
No resources available.