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RSS FeedsRemote Sensing, Vol. 9, Pages 979: Remote Sensing of Aerosol Optical Depth Using an Airborne Polarimeter over North China (Remote Sensing)


22 september 2017 15:21:01

Remote Sensing, Vol. 9, Pages 979: Remote Sensing of Aerosol Optical Depth Using an Airborne Polarimeter over North China (Remote Sensing)

The airborne Atmosphere Multi-angle Polarization Radiometer (AMPR) was employed to perform airborne measurements over North China between 2012 and 2016. Seven flights and synchronous ground-based observations were acquired. These data were used to test the sensor`s measurements and associated aerosol retrieval algorithm. According to the AMPR measurements, a successive surface-atmosphere decoupling based algorithm was developed to retrieve the aerosol optical depth (AOD). It works via an iteration method, and the lookup table was employed in the aerosol inversion. Throughout the results of the AMPR retrievals, the surface polarized reflectances derived from air- and ground-based instruments were well matched; the measured and simulated reflectances at the aircraft level, which were simulated based on in situ sun photometer observed aerosol properties, were in good agreement; and the AOD measurements were validated against the automatic sun-photometer (CE318) at the nearest time and location. The AOD results were close; the average deviation was less than 0.03. The MODIS AODs were also employed to test the AMPR retrievals, and they showed the same trend. These results illustrate that (i) the successive surface-atmosphere decoupling method in the retrieved program completed its mission and (ii) the aerosol retrieval method has its rationality and potential ability in the regionally accurate remote sensing of aerosol. Digg Facebook Google StumbleUpon Twitter
70 viewsCategory: Geology, Physics
Remote Sensing, Vol. 9, Pages 978: Raman Lidar Observations of Aerosol Optical Properties in 11 Cities from France to Siberia (Remote Sensing)
Remote Sensing, Vol. 9, Pages 982: Wuhan Surface Subsidence Analysis in 2015-2016 Based on Sentinel-1A Data by SBAS-InSAR (Remote Sensing)
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