Atmospheric correction for MASTER image data using localized modelled and observed meteorology and trace gases

Atmospheric correction for remote sensing-based studies typically does not use information from spatio-temporally resolved meteorological models. We assessed the effect of using observations and mesoscale weather and chemical transport models on multispectral retrievals of land and ocean properties. We performed two atmospheric corrections on image data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS)/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) airborne simulator over Monterey Bay, California. One correction used local atmospheric profiles of meteorology and trace gases at overpass and the other used the 1976 US Standard default atmospheric profile in the MODTRAN4 radiative transfer model.We found only minor impacts from atmospheric correction in the Fluorescence Line Height index of ocean chlorophyll, but substantive differences in retrievals of surface temperature and the Normalized Difference Vegetation Index. Improvements in sea surface temperature retrieval were validated by in situ measurements. Results indicate that spatio-temporally specific atmospheric correction factors from mesoscale models can improve retrievals of surface properties from remotely sensed image data

Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study

A41 Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study In: Addiction Science & Clinical Practice 2017, 12(Suppl 1): A4

A New Approach for Estimation of Fine Particulate Concentrations Using Satellite Aerosol Optical Depth and Binning of Meteorological Variables

9th Asian Aerosol Conference (AAC), Kanazawa, Japan, Jun 24-27, 2015Fine particulate matter (PM2.5) has recently gained attention worldwide as being responsible for severe respiratory and cardiovascular diseases, but point based ground monitoring stations are inadequate for understanding the spatial distribution of PM2.5 over complex urban surfaces. In this study, a new approach is introduced for prediction of PM2.5 which uses satellite aerosol optical depth (AOD) and binning of meteorological variables. AOD from the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) aerosol products, MOD04_3k Dark-Target (DT) at 3 km, MOD04 DT at 10 km, and MOD04 Deep-Blue (DB) at 10 km spatial resolution, and the Simplified Aerosol Retrieval Algorithm (SARA) at 500 m resolution were obtained for Hong Kong and the industrialized Pearl River Delta (PRD) region. The SARA AOD at 500 m alone achieved a higher correlation (R = 0.72) with PM2.5 concentrations than the MODIS C6 DT AOD at 3 km (R = 0.60), the DT AOD at 10 km (R = 0.61), and the DB AOD at 10 km (R = 0.51). The SARA binning model ([PM2.5] = 110.5 [AOD] + 12.56) was developed using SARA AOD and binning of surface pressure (996-1010 hPa). This model exhibits good correlation, accurate slope, low intercept, low errors, and accurately represents the spatial distribution of PM2.5 at 500 m resolution over urban areas. Overall, the prediction power of the SARA binning model is much better than for previous models reported for Hong Kong and East Asia, and indicates the potential value of applying meteorologicallyspecific empirical models and incorporating boundary layer height in operational PM2.5 forecasting from satellite AOD retrievals.Department of Land Surveying and Geo-Informatic

A New MODIS C6 Dark Target and Deep Blue Merged Aerosol Product on a 3 km Spatial Grid

In Moderate Resolution Imaging Spectroradiometer (MODIS) Collection (C6) aerosol products, the Dark Target (DT) and Deep Blue (DB) algorithms provide aerosol optical depth (AOD) observations at 3 km (DT3K) and 10 km (DT10K), and at 10 km resolution (DB10K), respectively. In this study, the DB10K is resampled to 3 km grid (DB3K) using the nearest neighbor interpolation technique and merged with DT3K to generate a new DT and DB merged aerosol product (DTB3K) on a 3 km grid using Simplified Merge Scheme (SMS). The goal is to supplement DB10K with high-resolution information over dense vegetation regions where DT3K is susceptible to error. SMS is defined as “an average of the DT3K and DB3K AOD retrievals or the available one with the highest quality flag”. The DT3K and DTB3K AOD retrievals are validated from 2008 to 2012 against cloud-screened and quality-assured AOD from 19 AERONET sites located in Europe. Results show that the percentage of DTB3K retrievals within the expected error (EE = ± (0.05 + 20%)) and data counts are increased by 40% and 11%, respectively, and the root mean square error and the mean bias are decreased by 26% and 54%, respectively, compared to the DT3K retrievals. These results suggest that the DTB3K product is a robust improvement over DT3K alone, and can be used operationally for air quality and climate-related studies as a high-resolution supplement to the current MODIS product suite