6 May 2016 A merged aerosol dataset based on MODIS and MISR Aerosol Optical Depth products
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Aerosol Optical Depth (AOD) products available from MODIS and MISR observations are widely used for aerosol characterization, and global/environmental change studies. These products are based on different retrieval-algorithms, resolutions, sampling, and cloud-screening schemes, which have led to global/regional biases. Thus a merged product is desirable which bridges this gap by utilizing strengths from each of the sensors. In view of this, we have developed a “merged” AOD product based on MODIS and MISR AOD datasets, using Bayesian principles which takes error distributions from ground-based AOD measurements (from AERONET). Our methodology and resulting dataset are especially relevant in the scenario of combining multi-sensor retrievals for satellite-based climate data records; particularly for long-term studies involving AOD. Specifically for MISR AOD product, we also developed a methodology to produce a gap-filled dataset, using geostatistical methods (e.g. Kriging), taking advantage of available MODIS data. Merged and spatially-complete AOD datasets are inter-compared with other satellite products and with AERONET data at three stations- Kanpur, Jaipur and Gandhi College, in the Indo-Gangetic Plains. The RMSE of merged AOD (0.08-0.09) is lower than MISR (0.11-0.20) and MODIS (0.15-0.27). It is found that merged AOD has higher correlation with AERONET data (r within 0.92-0.95), compared to MISR (0.74-0.86) and MODIS (0.69-0.84) data. In terms of Expected Error, the accuracy of valid merged AOD is found to be superior as percent of merged AOD within error envelope are larger (71-92%), compared to MISR (43-61%) and MODIS (50-70%).
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Manoj K. Singh, Manoj K. Singh, Ritesh Gautam, Ritesh Gautam, Parvatham Venkatachalam, Parvatham Venkatachalam, } "A merged aerosol dataset based on MODIS and MISR Aerosol Optical Depth products", Proc. SPIE 9876, Remote Sensing of the Atmosphere, Clouds, and Precipitation VI, 987627 (6 May 2016); doi: 10.1117/12.2223485; https://doi.org/10.1117/12.2223485

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