UROP Project Listing System
 
Project Title:
Retrival of Aerosol optical depth using machine learning algorithm
Supervisor:FUNG Jimmy Chi Hung
Co-Supervisor:FUNG Jimmy Chi Hung, LU Xingcheng
Quota:2
Project Description:Aerosol optical depth (AOD) is an important parameter for describing the aerosol impact on solar radiation. Due to the passing time of satellite and cloud effect, current AOD product has the issue of low time resolution (~1 day) and spatial incompleteness. In this project, we plan to combine machine learning method, ground observation data and numerical model simulation results to generate a high temporal resolution AOD product over the Pearl River Delta (PRD) region.
Course type:UROP1000 UROP1100 UROP2100  
Applicant's Roles:The applicants are expected to finish subjects in basic calculus and statistics, he/she should have a good programming skills. He/she will help the supervisor to conduct the numerical simulation part of the project.  
Applicant's Learning Objectives:Conclude the fundamental principles of AI and air quality. 
Complexity of the project:Moderate 
 



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