Remote Sensing Applications: Society and Environment 4 (2016) 158–166
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Remote Sensing Applications: Society and Environment journal homepage: www.elsevier.com/locate/rsase
Atmospheric correction assessment of SPOT-6 image and its influence on models to estimate water column transparency in tropical reservoir Luiz H.S. Rotta n, Enner H. Alcântara, Fernanda S.Y. Watanabe, Thanan W.P. Rodrigues, Nilton N. Imai São Paulo State University, Department of Cartography, 19060-900 Presidente Prudente, SP, Brazil
art ic l e i nf o
a b s t r a c t
Article history: Received 3 March 2016 Received in revised form 12 May 2016 Accepted 9 September 2016 Available online 10 September 2016
Remote sensing images have been increasingly used by its ability to collect data from extensive areas in a short time and with relatively low cost. Studies conducted in aquatic environments require great attention in relation to atmospheric correction, since the signal leaving water bodies is strongly attenuated. The present work aimed to assess the atmospheric correction of SPOT-6 image based on the variation of initial visibility parameter in FLAASH and analyze its influence on models to estimate Secchi depth (SD) and diffuse attenuation coefficient (Kd). The study was carried out in Nova Avanhandava Reservoir, which belongs to the chain of the Tietê River reservoirs (São Paulo, Brazil). The models calibration was based on remote sensing reflectance (Rrs) of simulated SPOT bands from data collected in the field. The best models were obtained using the band ratio Rrs(560 nm)/Rrs(660 nm) for SD (R2 ¼92%, RMSE ¼11.45%) and the band Rrs(660 nm) for Kd (R2 ¼ 92%, RMSE ¼11.98%). Maps of the spatial distribution of SD and Kd were made by applying the models on atmospherically corrected images. The main problem was the high amount of negative pixels when the suitable initial visibility value was not adopted in the atmospheric correction, which prevents the use of bio-optical models to retrieve limnological variables of the reservoir. & 2016 Elsevier B.V. All rights reserved.
Keywords: FLAASH Visibility Diffuse attenuation coefficient (Kd) Secchi depth (SD) Nova Avanhandava Reservoir
1. Introduction The radiation reflected or emitted by the Earth’s surface passes through the atmosphere, which interacts with several gases, water vapor and particulates. Thus, the radiation is influenced by the atmospheric scattering, absorption, reflection and refraction before being recorded by the remote sensing system (Jensen, 2009). Even when the sky is clear, the intensity of the solar beam is significantly reduced during its passage through the atmosphere (Kirk, 2011). In studies of aquatic environments, application of atmospheric corrections is recommended (Wang et al., 1999; Hu et al., 2001; Jamet et al., 2011), since the signal of the water bodies are significantly lower than vegetation, soil or anthropogenic targets, demanding greater accuracy in the correction process. The use of satellites to monitor the color of the water requires effective removal of the contribution of the atmosphere to the total signal measured by the remote sensor by atmospheric correction process (Jamet et al., 2011). Atmospheric correction over aquatic environments is generally more demanding than over land Corresponding author. E-mail addresses:
[email protected] (L.H.S. Rotta),
[email protected] (E.H. Alcântara),
[email protected] (F.S.Y. Watanabe),
[email protected] (T.W.P. Rodrigues),
[email protected] (N.N. Imai). n
http://dx.doi.org/10.1016/j.rsase.2016.09.001 2352-9385/& 2016 Elsevier B.V. All rights reserved.
because the signal from the water column is small (Hu et al., 2001). For Wang (1999), the atmospheric correction is a fundamental procedure in water color imagery data processing and remove about 90% of the signal measured by the sensor in the visible bands. Chen et al. (2007) ignored the atmospheric correction of TM-Landsat data because only one scene was used; however, the results are not comparable temporally or spatially. Usually, atmospheric correction is necessary. An algorithm to perform atmospheric correction of SeaWiFS data for turbid coastal waters has been described and tested by Ruddick et al. (2000). According to Hadjimitsis and Clayton (2009), the atmospheric correction must be done for the assessment of temporal variations of water quality. Many studies of aquatic environments have shown the importance of atmospheric correction using different satellite images such as Landsat (Hu et al., 2001; Giardino et al., 2001; Zheng et al., 2015), SPOT (Doxaran et al., 2002), MODIS (He and Chen, 2014), ENVISAT/ MERIS (Guanter et al., 2010), and SeaWiFS (Hu et al., 2000). Several studies have been conducted in order to evaluate different atmospheric correction methods, especially for aquatic environments. Bonansea et al. (2015) evaluated the potential of 6S radiative transfer model to improve the reliability for estimating water clarity in Río Tercero reservoir (Argentina). They demonstrated the usefulness of 6S code for atmospheric correction in Landsat data. The water clarity algorithm using surface reflectance
