The estimation of reflectance from hyperspectral data, a process called atmospheric correction, is a critical first step. Most of the methods need measurements of ground reflectances or atmosphere. When no information is available, unsupervised methods as Quick Atmospheric Correction (QUAC) exist assuming a large variability on the scene. But when studies on specific materials are conducted, no...

Mapping of vegetation in mountain areas based on remote sensing is obstructed by atmospheric and topographic distortions. A variety of atmospheric and topographic correction methods has been proposed to minimize atmospheric and topographic effects and should in principle lead to a better land cover classification. Only a limited number of atmospheric and topographic combinations has been tested...

Hyperspectral remote sensing is a powerful tool in discriminating lithological units and in preparation of mineral maps. Hyperion is a space borne sensor of Hyperspectral imagery having 220 channels within the 400 nm to 2500 nm wavelength range. Although the technical specifications of the sensor are quite high, in the operational stage there exist many nuisances like atmosphere. The presence o...

Microwave vegetation index (MVI) is a vegetation index defined in microwave bands. It has been developed based on observations from AMSR-E and widely used to monitor global vegetation. Recently, our study found that MVI was influenced by the atmosphere, although it was calculated from microwave bands. Ignoring the atmospheric influence might bring obvious uncertainty to the study of global vege...

A sensitivity study has been conducted to identify how radiometric noises and calibration errors on the level-1 top-of-atmosphere reflectances are propagated through the atmospheric correction and how they contribute to errors on the retrieved marine reflectances. Computations were performed using Monte-Carlo calculations and various atmospheric correction combinations were tested for typical a...

Water vapor content in the atmosphere is very significant for atmospheric correction of optical remote sensing data. Nowadays, the common atmospheric correction models use a single value of the average water vapor content of the study area to perform atmospheric correction. As the distribution of water vapor content varies greatly with time and space, it is obviously inaccurate to represent the...

The empirical ‘volcano-scan’ atmospheric correction is widely applied to martian near infrared CRISM and OMEGA spectra between ∼10 0 0 and ∼2600 nm to remove prominent atmospheric gas absorptions with minimal computational investment. This correction method employs division by a scaled empirically-derived atmospheric transmission spectrum that is generated from observations of the martian surfa...

To extract quantitative information from the Enhanced Thematic Mapper-Plus (ETM+) imagery accurately, atmospheric correction is a necessary step. After reviewing historical development of atmospheric correction of Landsat thematic mapper (TM) imagery, we present a new algorithm that can effectively estimate the spatial distribution of atmospheric aerosols and retrieve surface reflectance from E...

Atmospheric correction of satellite remote sensing image is the precondition of quantitative remote sensing study, and also among the difficulties of it. There are various methods and models for atmospheric correction. The author makes the atmospheric correction of SPOT-5 multi-spectrum remote sensing image covering Changsha, Zhuzhou and Xiangtan by adopting Model FLAASH and Model QUAC in the t...

The emergence of high-resolution satellites with new spectral channels and the ability to change its viewing angle has highlighted the importance of modeling the atmospheric effects. So, atmospheric correction serves a critical role in the processing of remotely sensed image data, particularly with respect to identification of pixel content. Efficient and accurate realization of images in units...