At the invitation of Associate Professor Huang Yinzhoufrom the College of Earth and Environmental Sciences, Lanzhou University, Associate Professor Yang Xuchao from the Ocean College, Zhejiang University, made an academic report on June 4, 2021.
Title: Spatial simulation of socio-economic data based on multi-source data and machine learning method
Time: June 4, 2021, 15:30.
Site: Lecture room 502, Qilian Building, Lanzhou University
Lecturer profile:
Yang Xuchao, associate professor and doctoral supervisor of the Ocean College, Zhejiang University. In 2008, he received his Ph.D. from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. His main research interests are climate change and urban environmental health, global change and coastal disaster risk. As the first author or corresponding author, he has published more than 30 SCI/SSCI papers in Environmental Health Perspectives, Environmental International, Environmental Science & Technology, Geophysical Research Letters, Journal of Geophysical Research-Atmospheres and other journals. He has presided over four NSFC projects, and his research achievements have been reported by nature as research highlights. He was awarded the World Meteorological Organization (WMO) Professor Mariolopoulos Trust Fund Award in 2012 / 2013.
Brief introduction of the report:
High resolution and accurate population and GDP data are the basis of refined disaster risk assessment. Based on the machine learning method, the multi-source remote sensing data and interest point (POI) data are integrated to simulate the population and GDP in the Chinese mainland. The grid dataset obtained can provide basic data support for fine disaster risk assessment and disaster prevention and mitigation. Based on the above methods, spatial simulation of electricity consumption and anthropogenic heat emissions in the Chinese mainland is carried out. These results can provide scientific and technological support for the scientific formulation of climate change mitigation policies and energy conservation and emission reduction.
