Biomass burning is a major problem in the Southeast Asian region. This anthropogenic haze occures very frequetly in this region due to drier weather conditions leading to an escalation in forest fire activities mainly over central Sumatra, Indonesia, and affected human health and other economic activities severely. This study has proposed an algorithm to estimate haze aerosol optical thickness (HAOT) in Peninsular Malaysia during the severe haze event in 2013 using MODIS 500m spatial resolution data in order to get a better understanding of the spatial distribution of the haze compared. The methodological consideration includes several steps of data processing i.e. i) haze identification, ii) haze LUT building using 6SV radiative transfer code, iii) AOT retrieval, and validation. Preliminary results indicate that haze aerosol optical thickness can be estimated from the MODIS 500 m data successfully with an accuracy more than 85% despite the problem of cloud cover. Further investigation is needed in order to understand the total potential of this algorithm by i) performing validation comparing with several data such as AERONET, Air Pollution Index (API), and Pollutant Standards Index (PSI) ii) investigating the effect of land surface reflectance on the HAOT estimation, and iii) applying robust cloud screening technique. However, from this initial outcome, it can be concluded that the limitations of point based estimation of air quality can be reduced using this algorithm and spatial distribution of HAOT can be investigated with a greater confidence level.
