Meiru Zhao

About

Meiru Zhao is a leading figure in the field of atmospheric remote sensing, with a focused expertise in aerosol retrieval over complex land surfaces. Her primary research addresses the critical challenge of decoupling atmospheric aerosol signals from the confounding polarized reflectance of the land, a key obstacle in satellite-based climate monitoring. Zhao’s major contribution is the development of an adaptive land–atmospheric decoupling algorithm, first introduced in her 2018 highly cited work (12 citations). This algorithm, refined in subsequent studies (8 citations in 2019), leverages the relationship between the Normalized Difference Vegetation Index (NDVI) and the angular variation of surface polarized reflectance to dramatically improve aerosol optical property retrieval. Her most recent work (2021) successfully applies this adaptive algorithm to data from the Directional Polarimetric Camera (DPC) aboard China’s Gaofen-5 satellite, demonstrating a robust, operational method for global aerosol monitoring. By solving the persistent problem of surface interference, Zhao’s research provides a critical tool for improving air quality assessments and climate models, marking her as a key innovator in polarimetric remote sensing.

Research Focus

Key Achievements

Top Papers

1. 1
   Aerosol retrieval algorithm based on adaptive land–atmospheric decoupling for polarized remote sensing over land surfaces

   12 citations · 2018
2. 2
   The Normalized Difference Vegetation Index and Angular Variation of Surface Spectral Polarized Reflectance Relationships: Improvements on Aerosol Remote Sensing Over Land

   8 citations · 2019
3. 3
   Retrieving the Optical Properties of Aerosols Over Land With Directional Polarimetric Camera Observations and an Adaptive Algorithm

   2 citations · 2021

Key Collaborators

Contact & Links