Recurrent transboundary pollution in Southeast Asia (SEA) from biomass burning poses a severe threat to this region. As a result, there is a need to develop a method for quantifying the aerosol due to biomass burning and their spatial distribution for the enhancement of the current aerosol monitoring techniques in SEA region. Therefore, this study develops an algorithm for the retrieval of biomass burning Haze Aerosol Optical Thickness (HAOT) by incorporating the following elements: i) MODIS 500 m data, ii) a robust radiative transfer code, iii) several combinations of land surface reflectance data, iv) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) forward analysis, v) effective cloud masking technique, and vi) image interpolation techniques. The results show strong agreement with the MODIS AOT product (r2 = 0.89–0.93), Aerosol Robotic Network (AERONET) AOT (r2 = 0.80–0.90), Air Pollution Index (API; r2 = 0.80–0.87), and Pollutant Standards Index (PSI; r2 = 0.90–0.93), which indicates that the proposed algorithm can retrieve HAOT, due to biomass burning, successfully. Although the HAOT algorithm was tested over a limited time from June 19 to June 28, 2013, the robust results suggest that in coordination with point-based measurements, HAOT can be used to improve the detection of aerosol induced haze. However, an adjustment will be necessary if this algorithm is used to retrieve haze aerosol optical thickness induced by biomass burning in different regions.