Atmospheric Correction of Optical Imagery

Quantitative remote sensing is an inevitable trend in the application of remote sensing in the 21st century. Its core role is to establish a quantitative relationship between the electromagnetic spectrum and the information obtained by the sensor and then use electromagnetic wave information to quantitatively detect all kinds of surface characteristic parameters. Quantitative remote sensing is based on the precise calibration of sensors and the atmospheric correction of remote sensing data. This chapter introduces the atmospheric effects on the process of remote sensing imaging and atmospheric correction to specifically discuss the utilization of atmospheric correction in processing remote sensing data. Section 1 presents the background of atmospheric effects. Section 2 discusses various algorithms for the estimation of aerosol properties, which are based on spectral, temporal, angular, spatial and polarization characteristics. Section 3 introduces the algorithms used for estimating atmospheric moisture content. Then, the influences of other atmospheric components and commonly used atmospheric correction models are illustrated. Finally, an application of atmospheric correction is presented.