Abstract

Water pixel extraction and correction of the atmospheric signal represent prerequisite steps prior to applying algorithms dedicated to the assessment of water quality of natural surface water bodies. The recent multiplication of medium spatial resolution sensors (10-60 m) provides the required constellation to monitoring bio-optical and biogeochemical parameters of surface waters at the relevant spatial-temporal scales. Here we present a new approach to identify water pixels and to extract the atmospheric contribution to the top of atmosphere signal measured by the NAOMI sensor on board the first Vietnamese satellite, VNREDSat-1. After verifying the TOA calibration of NAOMI through a vicarious calibration exercise, we adapt a recent water pixel extraction algorithm (WiPE) to NAOMI, and develop a new atmospheric correction algorithm (referred to as red-NIR) based on the use of the red and NIR bands (the only bands available for that purpose on NAOMI) and spectral relationships. The evaluation of red-NIR with a match-up data set gathering remote sensing reflectance, Rrs, measurements performed at the AERONET-OC stations in moderately turbid waters indicates excellent performance in the blue and green part of the spectrum (similar to the performances reached by the SeaDAS NIR-SWIR algorithms) and lower accuracy in the red. Intercomparison of simultaneous images collected by NAOMI and OLI over a more turbid water body shows an excellent agreement between the NAOMI-Rrs estimated by the present processing, and the OLI-Rrs estimated from the ACOLITE algorithm. This approach will allow sensors that do not have SWIR bands, such as SPOT-6 and -7, to be processed, making their data exploitation available for long-term temporal analyses.

Highlights

  • The tight societal and economical connections of Vietnam with the sea, mainly due to its 3260 km long coastline, makes this country very sensitive to natural and anthropogenic disasters

  • Intercomparison of simultaneous images collected by NAOMI and Operational Land Imager (OLI) over a more turbid water body shows an excellent agreement between the NAOMI-Rrs estimated by the present processing, and the OLI-Rrs estimated from the ACOLITE algorithm

  • Due to the unavailability of short-wave infrared (SWIR) bands on NAOMI, we developed a new atmospheric correction algorithm (Red-NIR) dedicated to the estimation of Rrs(λ) over coastal and inland waters

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Summary

Introduction

The tight societal and economical connections of Vietnam with the sea, mainly due to its 3260 km long coastline, makes this country very sensitive to natural and anthropogenic disasters. In order to use NAOMI images for aquatic applications over coastal and inland waters, water pixels have to be identified, while the top of atmosphere signal recorded by the sensor above these water surfaces has to be corrected from atmospheric effects This is the objective of the present study. A recent study emphasized that, among two current atmospheric correction algorithms developed for OLI (SeaDASS and ACOLITE), and tested over the AERONET-OC data set (i.e. over moderately turbid waters), SeaDAS performs better [33]. The adaptation and validation of the WiPE algorithm to NAOMI is presented, and the new atmospheric correction method based on the use of the red and NIR bands available on NAOMI is described.

Match-up data set
Radiometric in situ data set used for trans-spectral relationships
Statistical indicators of model performance
The water pixel extraction procedure for VNREDSat-1
Description of the atmospheric correction scheme
Match-up exercise for OLI based on the NAOMI configuration
Match-up exercise for VNREDSat-1
Intercomparison of NAOMI and OLI Rrs products over one turbid area
Findings
Concluding remarks
Full Text
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