Ultraviolet (UV) radiation has several effects on human health as well as other biological and chemical systems. The radiation can be weighted with the erythemal action spectrum and then converted to the dimensionless UV Index, which is designed to indicate the detrimental 'sunburning power' of the radiation for public heath purposes. A global view of the erythemally weighted irradiance from the Ozone Monitoring Instrument (OMI) on board the Aura spacecraft has been available since July, 2004. However, ground-based validation and correction of the satellite data are still required. In this thesis, the erythemal dose rates at local solar noon taken from the satellite were compared to ground-based data measured by spectroradiometers or broadband radiometers in two different climate areas: the Tropics and midlatitudes. This seeks to redress the lack of data and satellite validation for the Tropics, and also allows comparison with previous work in midlatitudes. The validation results show that the satellite data overestimates the ground-based data by 9%-32% at the cleanest site, with a much higher discrepancy at polluted sites. Using a radiative transfer model confirmed that the positive bias in the satellite data was mainly caused by aerosol absorption that is not taken into account in the satellite retrieval algorithm. Therefore, two empirical methods were introduced in order to correct the OMI UV data for absorbing aerosols under clear sky conditions. These methods required aerosol optical depth and aerosol single scattering, or aerosol absorption optical depth, as input parameters. The methods improved the OMI UV data by up to 30% depending on site and input data source. For cloudy conditions aerosol data is usually not available either from ground-based or satellite-based measurements; however, the effect of cloud is usually far greater than that of aerosol, and some of the aerosol effect (scattering) is intrinsically included in the cloud correction. A further empirical model for cloudy conditions was derived to reduce bias of the OMI UV data with respect to ground-based data. The method only requires the OMI UV data as an input. The cloudy model reduced the bias by about 13%-30% depending on site, and gave similar results even when used with clear sky data. Since ground-based data is sparse, the final goal of the work was to produce a corrected map of UV index for the whole of Thailand, based only on data available from satellite, which gives full regional coverage. Issues with availability and quality of satellite data meant that the best results were achieved by using only the cloudy sky correction, for all conditions. The resulting daily noontime UV Index maps of Thailand were assessed against ground-based data for independent years. The corrected UV Index was within ±2 compared with ground-based data for all sites, compared to discrepancies of up to 4 UV Index for uncorrected data.