Man Sing Wong

About

Dr. Man Sing Wong is a leading remote sensing scientist whose research centers on atmospheric aerosol and water vapor monitoring, with a particular focus on urban environments. His major contributions include developing innovative satellite-based algorithms to retrieve aerosol optical depth (AOD) at unprecedented spatial resolutions—from 500 m down to 160 m—enabling detailed air quality monitoring over complex urban areas like Hong Kong and the Pearl River Delta. His work on multi-sensor water vapor studies, integrating radiosonde, MODIS, and AERONET data, has advanced understanding of greenhouse gas dynamics and weather forecasting in monsoon regions. With over 375 citations across his most-cited papers, Dr. Wong's research has had significant impact, particularly his 2011 multi-sensor water vapor study (111 citations) and his 2014 aerosol retrieval improvement (66 citations). Notably, he has pioneered the use of Gaofen-1/6 satellite synergy for daily 160 m AOD retrieval, and extended his expertise to robotics with an automatic elevator button detection system for multi-story navigation. His work bridges satellite remote sensing, atmospheric science, and practical applications in public health and environmental monitoring.

Research Focus

Key Achievements

Top Papers

1. 1
   A multi‐sensor study of water vapour from radiosonde, MODIS and AERONET: a case study of Hong Kong

   111 citations · 2011
2. 2
   Improvement of aerosol optical depth retrieval over Hong Kong from a geostationary meteorological satellite using critical reflectance with background optical depth correction

   66 citations · 2014
3. 3
   Multi‐sensors study of precipitable water vapour over mainland China

   39 citations · 2014
4. 4
   Retrieval of Aerosol Optical Thickness Using MODIS $ \hbox{500} \times \hbox{500}\ \hbox{m}^{2}$, a Study in Hong Kong and the Pearl River Delta Region

   38 citations · 2010
5. 5
   Improved aerosol retrieval algorithm using Landsat images and its application for PM10 monitoring over urban areas

   32 citations · 2014
6. 6
   Retrieval of dust storm aerosols using an integrated Neural Network model

   24 citations · 2015
7. 7
   Estimation of aerosol sources and aerosol transport pathways using AERONET clustering and backward trajectories: a case study of Hong Kong

   22 citations · 2012
8. 8
   Automatic Elevator Button Localization Using a Combined Detecting and Tracking Framework for Multi-Story Navigation

   21 citations · 2020
9. 9
   First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation

   13 citations · 2024
10. 10
    Monitoring 2.5 μm particulate matter within urbanized regions using satellite-derived aerosol optical thickness, a study in Hong Kong

    9 citations · 2011

Key Collaborators

Contact & Links