Abstract
Water color remote sensing requires accurate atmospheric correction but this remains a significant challenge in highly turbid waters. In this respect, the shortwave infrared (SWIR) band-based atmospheric correction approach has proven advantageous when applied to the moderate resolution imaging spectroradiometer (MODIS) onboard the Aqua satellite. However, even so, uncertainties affect its accuracy. We performed a regional vicarious calibration of the MODIS-Aqua SWIR (1240, 2130)-based atmospheric correction using in situ water surface reflectance data measured during different seasons in Lake Taihu, a highly turbid lake. We then verified the accuracy of the (1240, 2130)-based atmospheric correction approach using these results; good results were obtained for the remote sensing reflectance retrievals at the 555, 645, and 859 nm, with average relative errors of 15%, 14%, and 22%, respectively, and no significant bias. Comparisons with the (1240, 2130)-based iterative approach and (1640, 2130)-based approach showed that the vicarious calibrated (1240, 2130)-based approach has the best accuracy and robustness. Thus, it is applicable to the highly turbid Lake Taihu. It may also be applicable to other highly turbid inland waters with similar optical and aerosol optical properties above water, but such applications will require further validation.
Highlights
Water color satellite sensors receive top-of-atmosphere (TOA) radiance, which includes water-leaving and atmospheric path radiance
Water-leaving radiance, which can be used to assess water parameters, must be derived from satellite-received TOA radiance [1]. This process is known as atmospheric correction, which is the basis for water color remote sensing
Previous studies have applied this approach to the sea-viewing wide field-of-view sensor (SeaWiFS) and the moderate-resolution imaging spectroradiometer (MODIS), which have all yielded good results in open ocean waters [2]
Summary
Water color satellite sensors receive top-of-atmosphere (TOA) radiance, which includes water-leaving and atmospheric path radiance. Water-leaving radiance, which can be used to assess water parameters, must be derived from satellite-received TOA radiance [1]. Gordon and Wang [1] proposed an atmospheric correction approach (abbreviated as GW94) based on the “black near-infrared (NIR) water-leaving radiance” assumption This approach uses two NIR bands to assess aerosol radiance and interpolates the aerosol radiance to visible (VIS) bands. The second approach uses atmospheric information derived from adjacent clear water and interpolates the corrections to the turbid water [8] These improved approaches usually work well in moderately turbid waters but are not necessarily valid for highly turbid waters since certain waters saturate the NIR bands, rendering these “black NIR”-based approaches completely unusable
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