Development of the models to estimate particulate matter from thermal infrared band of Landsat Enhanced Thematic Mapper

Abstract

Particulate matter concentration and assessment of its movement pattern is crucial in air pollution studies. However, no study has been conducted to determine the PM10 concentration using atmospheric correction of thermal band by temperature of nearest dark pixels group (TNDPG) of this band. For that purpose, 16 Landsat Enhanced Thematic Mapper plus ETM+ images for Sanandaj and Tehran in Iran were utilized to determine the amount of PM10 concentration in the air. Thermal infrared (band 6) of all images was also used to determine the ground station temperature (GST b6) and temperature of nearest dark pixels group. Based on atmospheric correction of images using temperature retrieval from Landsat ETM+, three empirical models were established. Non-linear correlation coefficient with polynomial equation was used to analyze the correlations between particulate matter concentration and the ground station temperature for the three models. Similar analyses were also undertaken for three stations in Klang Valley, Malaysia, using 11 Landsat ETM+ images to show the effectiveness of the model in different region. The data analysis indicated a good correlation coefficient R = 0.89 and R = 0.91 between the trend of the result of temperature of nearest dark pixels group b6 − (GST b6 − GST) model and the trend of PM10 concentration in Iran and Malaysia, respectively. This study reveals the applicability of the thermal band of Landsat TM and ETM+ to determine the PM10 concentration over large areas.