Comparison of atmospheric correction algorithms for TM image in inland waters

Abstract

In order to extract quantitative water-leaving information from the Thematic Mapper (TM) image accurately in inland waters, atmospheric correction is a necessary step. Based on former researchers' results, the paper presents two atmospheric correction algorithms based on meteorological data (MD) and on Moderate Resolution Imaging Spectroradiometer (MODIS) Vicarious Calibration (MVC) for TM image in inland waters according to the theory of radiative transfer. Studying Taihu lake, China, in this paper we derived water remote sensing reflectance from a TM image of 26 July 2004 by these two atmospheric correction algorithms and we compare the results with that of dark object subtraction (DOS) and 6S code. The results show that the effect of atmospheric correction based on meteorological data and MODIS Vicarious Calibration is much better than that of DOS and 6S code. Although the MD is more accurate, MVC may be an ideal choice for TM images in inland water because TERRA MODIS images can be acquired easily than collecting meteorological data at the time of satellites passing over.

Atmospheric correction issues for retrieving total suspended matter concentrations in inland waters using OLI/Landsat-8 image

“…However, the minimum value identified in each band is strongly dependent on quantity and composition of TSM concentration present within the aquatic system. Other effects, such as specular reflection and whitecaps (Gong et al, 2008), also affect the minimum value assumed for a black pixel. In the BBHR, maybe we cannot to consider the ''blackpixel" assumption since the reflectance in OLI3 or OLI4 are high due to high levels of Chl-a or other OSCs with high reflectances in those spectral regions.…”

“…The atmospheric correction has been extensively discussed to focus on modeling the aerosol/gases contributions to the R rs from the signal registered by sensors (Chavez, 1988;Vermote and Vermeulen, 1999;Vermote et al, 2006, Ruddick et al, 2000Moses et al, 2012;Goyens et al, 2013). Moreover, several studies have been conducted to evaluate what improvements are achieved when the atmospheric corrections are used in images over aquatic systems (Gong et al, 2008;Moses et al, 2012;Bonansea et al, 2015;Vanhellemont and Ruddick, 2015;Rotta et al, 2016). There are several atmospheric correction algorithms available (Berk et al, 1998;Adler-Golden et al, 1999;Matthew et al, 2000;Ruddick et al, 2000;Bernstein et al, 2013;Vanhellemont and Ruddick, 2015;Richter and Schläpfer, 2016) and code implemented in softwares of image processing, but there is no consensus about which one should be used for remote sensing of the water color.…”

Retrieving the Lake Trophic Level Index with Landsat-8 Image by Atmospheric Parameter and RBF: A Case Study of Lakes in Wuhan, China

“…Some typical methods of this category are 6S (Second Simulation of the Satellite Signal in the Solar Spectrum), FLAASH (Fast Line-of-sight Atmospheric Analysis Spectral Hypercubes), ATCOR (ATmospheric CORection), HATCH (High-accuracy Atmospheric Correction for Hyperspectral Data), and BRDF (Bidirectional Reflectance Distribution Function) [23]. The accuracy of the radiative transfer modelling approach is very high in the case of known atmospheric data, but the application of this atmospheric correction algorithm is often limited by the real-time measurement of atmospheric parameters at the corresponding time of satellite transit [26,33].…”

MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA

“…Moreover, any attempts to apply more realistic atmospheric correction schemes, including the direct and diffuse light fluxes and aerosol light scattering simulations [46][47][48][49], resulted in even poorer results. The additional complexity associated with the atmospheric correction applied in this study, likely did not adequately represent atmospheric optical processes to the extent necessary to result in a measurable improvement in WQCs retrievals.…”

“…Without additional information the development of a substantially complete version of atmospheric correction sub-algorithm was not possible [46][47][48][49]. Therefore, two approaches, one that incorporated a very simple atmospheric correction and one without any atmospheric correction were developed and tested.…”