Back to Search Start Over

Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter

Authors :
Doubovik, Oleg
Jin, Shikuan
Ma, Yingying
Zhang, Ming
Gong, Wei
Dubovik, Oleg
Liu, Boming
Shi, Yifan
Yang, Changlan
Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA)
Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)
Source :
Remote Sensing, Remote Sensing, MDPI, 2019, 11 (19), pp.2218. ⟨10.3390/rs11192218⟩, Remote Sensing, 2019, 11 (19), pp.2218. ⟨10.3390/rs11192218⟩, Remote Sensing, Vol 11, Iss 19, p 2218 (2019)
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

International audience; Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products are used worldwide for their reliable accuracy. However, the aerosol optical depth (AOD) usually retrieved by the operational dark target (DT) algorithm of MODIS has been missing for most of the urban regions in Central China. This was due to a high surface reflectance and heavy aerosol loading, especially in winter, when a high cloud cover fraction and the frequent occurrence of haze events reduce the number of effective satellite observations. The retrieval of the AOD from limited satellite data is much needed and important for further aerosol investigations. In this paper, we propose an improved AOD retrieval method for 500 m MODIS data, which is based on an extended surface reflectance estimation scheme and dynamic aerosol models derived from ground-based sun-photometric observations. This improved method was applied to retrieve AOD during heavy aerosol loading and effectively complements the scarcity of AOD in correspondence with urban surface of a higher spatial resolution. The validation results showed that the retrieved AOD was consistent with MODIS DT AOD (R =~0.87; RMSE =~0.11) and ground measurements (R =~0.89; RMSE =~0.15) from both the Terra and the Aqua satellite. The method can be easily applied to different urban environments affected by air pollution and contributes to the research on aerosol.

Details

Language :
English
ISSN :
20724292
Database :
OpenAIRE
Journal :
Remote Sensing, Remote Sensing, MDPI, 2019, 11 (19), pp.2218. ⟨10.3390/rs11192218⟩, Remote Sensing, 2019, 11 (19), pp.2218. ⟨10.3390/rs11192218⟩, Remote Sensing, Vol 11, Iss 19, p 2218 (2019)
Accession number :
edsair.doi.dedup.....34aba428b90c2560cded8e9819fb4403