Description of a New Method for Retrieving the Aerosol Optical Thickness from Satellite Remotely Sensed Imagery Using the Maximum Contrast Value and Darkest Pixel Approach

Abstract

Satellite sensors have provided new datasets for monitoring regional and urban air quality. Satellite sensors provide comprehensive geospatial information on air quality with both qualitative remotely sensed imagery and quantitative data, such as aerosol optical depth which is the basic unknown parameter for any atmospheric correction method in the pre-processing of satellite imagery. This article presents a new method for retrieving aerosol optical thickness directly from satellite remotely sensed imagery for short wavelength bands in which atmospheric scattering is the dominant contribution to the at-satellite recorded signal. The method is based on the determination of the aerosol optical thickness through the application of the contrast tool (maximum contrast value), the radiative transfer calculations and the 'tracking' of the suitable darkest pixel in the scene. The proposed method that needs no a-priori information has been applied to LANDSAT-5 TM, LANDSAT-7 ETM + , SPOT-5 and IKONOS data of two different geographical areas: West London and Cyprus. The retrieved aerosol optical thickness values show high correlations with in-situ visibility data acquired during the satellite overpass. Indeed, for the West London area a logarithmic regression was fitted for relating the determined aerosol optical thickness with the in-situ visibility values. A high correlation coefficient ( r 2 = 0.82; p = 0.2) was found. Plots obtained from Tanre et al. (1979) and Forster (1984 were reproduced and estimates for these areas were generated with the proposed method so as to compare the results. The author's results show good agreement with Forster's aerosol optical thickness vs. visibility results and a small deviation from Tanre's model estimates.

The use of selected pseudo-invariant targets for the application of atmospheric correction in multi-temporal studies using satellite remotely sensed imagery

“…The aerosol optical thickness has been measured in situ using sun-photometers from a going-research project as a tool for assessing the atmospheric pollution in the Paphos District area in Cyprus (Hadjimitsis, 2008;Hadjimitsis et al, 2008a). The proposed method has been applied to a recent Landsat-T ETM+ image acquired on the August 13, 2008 to retrieve the aerosol optical thickness.…”

Assessment of temporal variations of water quality in inland water bodies using atmospheric corrected satellite remotely sensed image data

“…The separation of contributions is not known a priori, so the objective of atmospheric correction is to quantify these two components so that the main analysis can made on the correct target reflectance or radiance values. The darkest pixel (DP) atmospheric correction method, also termed histogram minimum method (Hadjimitsis 1999(Hadjimitsis , 2008Hadjimitsis et al 2000bHadjimitsis et al , 2003Hadjimitsis et al , 2004Hadjimitsis et al , 2006Hadjimitsis and Clayton 2008), was applied to the eight satellite images of the Lower Thames Valley reservoirs. The DP method was found to produce reservoir reflectance values within the range of ground measurements acquired in the reservoirs using a field GER1500 field spectro-radiometer Hadjimitsis et al (2004).…”

Air Pollution Monitoring Using Earth Observation & GIS

“…Hadjimitsis (2009a) used a new method for determining AOT through the use of the darkest pixel atmospheric correction over the London Heathrow Airport area in the UK and the Pafos Airport area in Cyprus. Hadjimitsis (2009b) developed a method to determine the aerosol optical thickness through the application of the contrast tool (maximum contrast value), the radiative transfer calculations and the 'tracking' of the suitable darkest pixel in the scene for Landsat, SPOT and high resolution imagery such as IKONOS and Quickbird.…”