WE3.R16.4
AN OPT3D-ASSISTED FUSION METHOD FOR MT-INSAR GEOCODING CORRECTION
Siying Li, Fengming Hu, Xiaole Ye, Jiaxin Mao, Yiming Chen, Shiyao Su, Fudan University, China
Session:
WE3.R16: Urban: Urban Dynamics, Land Use, and Social Impacts IV Oral
Track:
Land Applications
Location:
Lincoln East
Presentation Time:
Wednesday, 12 August, 14:30 - 14:45
Session Chair:
Maxwell Owusu, University of Twente
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Session WE3.R16
WE3.R16.1: Mapping deprived areas in a heterogeneous urban environment using a machine learning density cluster approach
Maxwell Owusu, Monika Kuffer, University of Twente, Netherlands; Ryan Engstrom, The George Washington University, United States; Mariana Belgiu, Karin Pfeffer, University of Twente, Netherlands
WE3.R16.2: A Deep Learning–Based Approach for Parcel-Level Inefficient Land Identification Using High-Resolution Remote Sensing: A Case Study of Jinan
Jinhong Yu, Hao Wang, Chinese Academy of Surveying and Mapping, China; Wenhao Li, Shandong University of Science and Technology, China; Caijuan Liu, Ruiqian Zhang, Xiaogang Ning, Chinese Academy of Surveying and Mapping, China
WE3.R16.3: MACHINE LEARNING DRIVEN MULTI-SENSOR AND BUILT-FORM FUSION USING SELF-ORGANIZING MAPS FOR URBAN ENVIRONMENTAL STRESS MAPPING IN LAHORE
Asfra Rizwan Toor, Hajra Javed, Zubair Khalid, Lahore University of Management Sciences, Pakistan
WE3.R16.4: AN OPT3D-ASSISTED FUSION METHOD FOR MT-INSAR GEOCODING CORRECTION
Siying Li, Fengming Hu, Xiaole Ye, Jiaxin Mao, Yiming Chen, Shiyao Su, Fudan University, China
Resources
No resources available.