RESUMO
Satellite remote sensing of coastal waters is important for understanding the functioning of these complex ecosystems. High satellite revisit frequency is required to permit a relevant monitoring of the strong dynamical processes involved in such areas, for example rivers discharge or tidal currents. One key parameter that is derived from satellite data is the suspended particulate matter (SPM) concentration. Knowledge of the variability of SPM could be used by sediment transport models for providing accurate predictions. Most of the current satellites that are dedicated to ocean color observations have a sun-synchronous orbit that performs a single daytime observation. The Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color sensor (NASA/NOAA) is the only one that is equipped with a panchromatic spectral band, so-called Day-Night Band, which is able to measure extremely low level signals, typically of the order of magnitude of 10-5 W m-2 sr-1µm-1. The objective of this paper is to investigate the potential of the panchromatic and radiometric specifications of the VIIRS sensor to detect SPM concentrations from nighttime satellite observations. Realistic radiative transfer simulations are performed to quantitatively determine the amplitude of the top of atmosphere radiances under various conditions such as various moon incident illuminations, observation geometries, atmospheric and oceanic turbidities. The simulations are compared with the minimum detectable radiance as specified for the VIIRS sensor. The results show that the detection of SPM is systematically feasible, including in clear waters, for any observation geometries in the case of a full moon illumination. The sensitivity of the results to the lunar phase (i.e., out of the full moon conditions), which is one of the originalities of the study, shows that the detection should also be feasible for a significant number of nights over the entire lunar cycle, typically from 5 to 15 nights depending on the water turbidity. Therefore, nighttime ocean color panchromatic measurements performed using a VIIRS-like sensor are a highly promising approach, especially if it is combined with daytime observations, for improving the monitoring of ocean dynamics.
RESUMO
The estimation of the bathymetry and the detection of targets located on the seabed of shallow waters using remote sensing techniques is of great interest for many environmental applications in coastal areas such as benthic habitat mapping, monitoring of seabed aquatic plants and the subsequent management of littoral zones. For that purpose, knowledge of the optical effects induced by the neighborhood of a given seabed target and by the water column itself is required to better interpret the subsurface upward radiance measured by satellite or shipborne radiometers. In this paper, the various sources of photons that contribute to the subsurface upward radiance are analyzed. In particular, the adjacency effects caused by the neighborhood of a given seabed target are quantified for three water turbidity conditions, namely clear, moderately turbid and turbid waters. Firstly, an analytical expression of the subsurface radiance is proposed in order to make explicit the radiance terms corresponding to these effects. Secondly, a sensitivity study is performed using radiative transfer modeling to determine the influence of the seabed adjacency effects on the upward signal with respect to various parameters such as the bathymetry or the bottom brightness. The results show that the highest contributions of the adjacency effects induced by the neighborhood of a seabed target to the subsurface radiance could reach 26%, 18% and 9% for clear, moderately turbid and turbid water conditions respectively. Therefore, the detection of a seabed target could be significantly biased if the seabed adjacency effects are ignored in the analysis of remote sensing measurements. Our results could be further used to improve the performance of inverse algorithms dedicated to the retrieval of bottom composition, water optical properties and/or bathymetry.
RESUMO
We present an analytical approach based on Cramer-Rao Bounds (CRBs) to investigate the uncertainties in estimated ocean color parameters resulting from the propagation of uncertainties in the bio-optical reflectance modeling through the inversion process. Based on given bio-optical and noise probabilistic models, CRBs can be computed efficiently for any set of ocean color parameters and any sensor configuration, directly providing the minimum estimation variance that can be possibly attained by any unbiased estimator of any targeted parameter. Here, CRBs are explicitly developed using (1) two water reflectance models corresponding to deep and shallow waters, resp., and (2) four probabilistic models describing the environmental noises observed within four Sentinel-2 MSI, HICO, Sentinel-3 OLCI and MODIS images, resp. For both deep and shallow waters, CRBs are shown to be consistent with the experimental estimation variances obtained using two published remote-sensing methods, while not requiring one to perform any inversion. CRBs are also used to investigate to what extent perfect a priori knowledge on one or several geophysical parameters can improve the estimation of remaining unknown parameters. For example, using pre-existing knowledge of bathymetry (e.g., derived from LiDAR) within the inversion is shown to greatly improve the retrieval of bottom cover for shallow waters. Finally, CRBs are shown to provide valuable information on the best estimation performances that may be achieved with the MSI, HICO, OLCI and MODIS configurations for a variety of oceanic, coastal and inland waters. CRBs are thus demonstrated to be an informative and efficient tool to characterize minimum uncertainties in inverted ocean color geophysical parameters.