Air quality monitoring is needed to control air pollution in urban areas. A limited number of air quality monitoring stations, limits the initial strategy of pollution prevention program in Malaysia in air quality monitoring especially at micro-scale level. The technique used to monitor air quality involves manual measurement of pollution concentrations within the area of measuring station. A more practical approach is needed to study air quality at micro-scale. One possibility is the use of satellite remote sensing and Geographical Information System (GIS) technologies. This paper present results obtained from research carried out to assess the suitability of satellite remote sensing and GIS techniques for air quality monitoring. Although three different datasets were used in the research, only results obtained from the Landsat 7 Enhance Thematic Mapper Plus (ETM+) dataset dated the 15th of July 2000 will be described. Eight (8) Continuous Air Quality Monitoring (CAQM) data are used to determine the relationship between digital number (DN) of the thermal infrared band and four pollutant parameters, i.e. Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), Carbon Monoxide (CO2) and Particulate Matters (particles less than 10 micron in size – PM10). The study area for this research covers the whole of Klang Valley Region. A limited area, which covers only part of the Shah Alam city is used for micro scale study. Since there are limited numbers of CAQM stations available, the concept of “Virtual Stations” is introduced to densify these stations. Based on derived pollutant values of these stations, kriging interpolation method is used to generate the pollutant maps of different pollutant parameters of the study area. Results from this research have indicated that SO2, NO2, CO and PM10 have positive correlation with digital number of the thermal infrared band. Initial analysis has shown that there is a strong correlation between satellite digital number (thermal band) and SO2 pollutant. Maps of pollution concentration generated from virtual stations using kriging interpolation method produce a more realistic distribution of air pollution. The concentration of SO2, NO2, CO and PM10 are highest in the industrial zones of Shah Alam.