This thesis presents a new technique to identify a 2D mask showing the extent of particulate aerosol distributions in satellite imagery. This technique uses a supervised texture classication approach, and utilises data from two distinct satellite sources. The vertical feature mask (VFM) product from the CALIPSO lidar, provides an accurate description of the aerosol content of the atmosphere but has a limited footprint and coverage. The CALIPSO VFM is used to provide training data in order to for classiers to be applied to other imagery, namely data from the spinning enhanced visible and infrared imager (SEVIRI) on the MSG satellite. The output from the classication is a 2D mask representing the locations of the particulate aerosol of interest within the SEVIRI image. This approach has been demonstrated on test cases over land and ocean, and shows a good agreement with other techniques for the detection of particulate aerosol. However, the supervised texture approach provides outputs at a higher resolution than the existing methods and the same approach is applicable over land and ocean and therefore shows the advantages compared to the current techniques. Furthermore, the coverage of the approach can be further extended using signature extension and chain classication. Signature extension was applied to one of the test cases to monitor the same geographical region with temporal extension away from the initial supervised classication. The experiments showed that it was possible to extend the coverage for ±90 minutes from the original classication and indicates the possibility of greater extension over larger temporal windows.

The Moderate-resolution Imaging Spectroradiometer (MODIS) onboard NASA’s Terra and Aqua satellites have provided a global distribution of aerosols. The space-based inversion of MODIS measurements requires assumption about the surface and aerosol properties, both are highly heterogeneous in space and time. This thesis has investigated the role of surface reflectance and aerosol properties on the retrieval of aerosols from MODIS over the Indian region. The aerosol properties retrieved by MODIS including total aerosol optical depth (AOD) and aerosol fine mode fraction (AFMF, fractional contribution of fine mode aerosols in the total AOD) were compared with that obtained from Aerosol Robotic Network (AERONET) at Kanpur (26.45◦N,80.35◦E), Indo-Gangetic Basin, northern India. This region is a special region for the study of aerosols as it offers strong aerosol seasonality, where the region is influenced by dust aerosols during pre-monsoon (March to June) and dominated by the fine mode particles in winter (November to February). The MODIS Collection 004 (C004) aerosol products systematically overestimated AOD in the presence of dust and underestimated when fine particles were dominant. The errors in the retrieval of dust AOD were correlated with the apparent reflectance at 2.1 µm, from which the surface reflectance in the visible channels (0.47 µm and 0.66 µm) were estimated using the “dark target” spectral correlation method. The error in the retrieval of AOD were also found to be large in the scattering angle range 120◦150◦, where the scattering properties of the non-spherical dust aerosols differ from that of the assumed spherical particles. AFMF of C004 was found to be highly biased to fine mode at Kanpur. The Collection 005 (C005) aerosol retrieval of the second-generation aerosol algorithm, however, showed improved retrieval of spectral AOD, which is likely to be attributed to the use of updated aerosol models and parameterized surface reflectance. In contrast to the C004 products, fine AOD and fine-model weighting (FMW) of C005 were biased very low at Kanpur and also over the greater Indian land region. This has indicated that the inversion of the space-based MODIS measurements is non-unique in which an improper combination of surface reflectance and aerosol model provide more accurate retrieval of the total aerosol optical depth. The surface reflectance relationships between the visible and shortwave-infrared 2.1 µm channels derived from the actual measurements of the surface reflectance using a spectroradiometer onboard an aircraft over Bangalore (12.95◦N,77.65◦E) in the southern India were found to have higher slope and intercept than that assumed by the MODIS algorithm over the same region. The high spectral correlations between the measured reflectance at longer wavelengths indicated some potential to estimate the surface reflectance at these wavelengths which needs further investigation. An experiment on the retrieval of aerosols carried out with several combinations of aerosol models and visible surface reflectance clearly shown that the surface reflectance in the visible channels assumed in the MODIS aerosol algorithm should be increased from its current parameterization in order to retrieve more accurate total as well as size-segregated aerosol optical properties at Kanpur and also over the greater Indian land region. In addition to the visible channels, inclusion of longer wavelengths in the aerosol inversion would likely improve the accuracy of retrieval over land by resolving the spectral dependence of aerosols. This in turn can help in separating the anthropogenic and natural aerosols in the total aerosol loading.