**1. Introduction**

Aerosol optical thickness (AOT) is defined as the degree to which aerosols prevent the transmission of light through absorption or scattering of light. AOT can be retrieved by using radiometers on board satellites [1–3], ground-based sunphotometers, and satellite sensors, such as the moderate resolution imaging spectroradiometer(MODIS), which provide AOT measurements on a daily and monthly basis [4, 5]. However, the spatial resolution of the MODIS AOT data products is 10 × 10 km, which does not permit the identification of specific AOT distribution over urban areas or complex terrains [5–7]. Due to the variability of aerosols, atmospheric aerosol monitoring is difficult. Significant efforts to improve aerosol

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

characterizations have included using *in-situ* measurements, ground-based remote sensing, and satellite observations [1–3]. AOT derived from satellite images often requires further validation [8]. The accuracy of satellite-derived AOT is frequently assessed by comparing satellite-based AOT with **AE**rosol **RO**botic **NET**work (AERONET, a program established by **NASA**) or field-based sun photometers [9, 10].

Research indicates that the determined AOT from satellite image data can be used as a tool to assess air pollution as well as identify the sources of local emissions [2, 7, 11–24]. AOT values can be used as a way of measuring air quality; determining AOT in large-scale pollution areas provides a synoptic, cost-effective means to further assess the air quality in such areas [16, 18– 24]. Indeed, the AOT values derived from the atmospheric path radiance can be utilized to assess and monitor air quality and atmospheric pollution [8]. The image-based integrated method presented in this chapter can accurately calculate AOT values retrieved from satellite imagery by using radiative transfer (RT) equations and GIS. The method can be used to visually display AOT levels using thematic maps in order to identify concentrations of AOT over an urban area [11]. The image-based method can also be used with archived satellite images, thereby providing detailed information regarding spatial aerosol concentration overtime [11].

AOT is directly related to the atmospheric aerosol load, which is the main variable describing the effects of aerosols on radiative transfer in the Earth's atmosphere. According to Guanter et al. [25], modeling atmospheric constituents and surface reflectance involves modeling the radiative transfer across the atmosphere. The key parameter for assessing atmospheric pollution is the aerosol optical thickness, which is also the most important unknown of every atmospheric correction algorithm for solving the radiative transfer equation and removing atmospheric effects from remotely sensed satellite images [8, 26–29]. Several researchers [5, 18, 26, 28, 29–37] found that using the radiative transfer and atmospheric modeling in conjunction with field measurements of aerosol optical thickness can yield more accurate atmospheric corrections instead of using simple image-based techniques.

The image-based integrated method discussed in this chapter combines the RT equation, satellite imagery, the modified darkest pixel (DP) method of atmospheric correction, and GIS to derive AOT measures. An example including 11 Landsat satellite images with *insitu* measurements over a specific period of time is used to assess the AOT values based on the 30 × 30 m spatial resolution of Landsat over the city of Limassol, Cyprus and create thematic maps to display the AOT levels.
