scholarly journals An Algorithm to Estimate Suspended Particulate Matter Concentrations and Associated Uncertainties from Remote Sensing Reflectance in Coastal Environments

2020 ◽  
Vol 12 (13) ◽  
pp. 2172 ◽  
Author(s):  
Juliana Tavora ◽  
Emmanuel Boss ◽  
David Doxaran ◽  
Paul Hill
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Ocean Color ◽  
Major Constituent ◽  
Coastal Environments ◽  
Suspended Particulate ◽  
Spm Concentration

Suspended Particulate Matter (SPM) is a major constituent in coastal waters, involved in processes such as light attenuation, pollutant propagation, and waterways blockage. The spatial distribution of SPM is an indicator of deposition and erosion patterns in estuaries and coastal zones and a necessary input to estimate the material fluxes from the land through rivers to the sea. In-situ methods to estimate SPM provide limited spatial data in comparison to the coverage that can be obtained remotely. Ocean color remote sensing complements field measurements by providing estimates of the spatial distributions of surface SPM concentration in natural waters, with high spatial and temporal resolution. Existing methods to obtain SPM from remote sensing vary between purely empirical ones to those that are based on radiative transfer theory together with empirical inputs regarding the optical properties of SPM. Most algorithms use a single satellite band that is switched to other bands for different ranges of turbidity. The necessity to switch bands is due to the saturation of reflectance as SPM concentration increases. Here we propose a multi-band approach for SPM retrievals that also provides an estimate of uncertainty, where the latter is based on both uncertainties in reflectance and in the assumed optical properties of SPM. The approach proposed is general and can be applied to any ocean color sensor or in-situ radiometer system with red and near-infra-red bands. We apply it to six globally distributed in-situ datasets of spectral water reflectance and SPM measurements over a wide range of SPM concentrations collected in estuaries and coastal environments (the focus regions of our study). Results show good performance for SPM retrieval at all ranges of concentration. As with all algorithms, better performance may be achieved by constraining empirical assumptions to specific environments. To demonstrate the flexibility of the algorithm we apply it to a remote sensing scene from an environment with highly variable sediment concentrations.

scholarly journals A Simple Empirical Band-Ratio Algorithm to Assess Suspended Particulate Matter from Remote Sensing over Coastal and Inland Waters of Vietnam: Application to the VNREDSat-1/NAOMI Sensor

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2636
Author(s):  
Dat Dinh Ngoc ◽  
Hubert Loisel ◽  
Vincent Vantrepotte ◽  
Huy Chu Xuan ◽  
Ngoc Nguyen Minh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Band Ratio ◽  
Data Set ◽  
Spectral Bands ◽  
Processing Chain ◽  
Suspended Particulate ◽  
Data Points ◽  
Spm Concentration

VNREDSat-1 is the first Vietnamese satellite enabling the survey of environmental parameters, such as vegetation and water coverages or surface water quality at medium spatial resolution (from 2.5 to 10 m depending on the considered channel). The New AstroSat Optical Modular Instrument (NAOMI) sensor on board VNREDSat-1 has the required spectral bands to assess the suspended particulate matter (SPM) concentration. Because recent studies have shown that the remote sensing reflectance, Rrs(λ), at the blue (450–520 nm), green (530–600 nm), and red (620–690 nm) spectral bands can be assessed using NAOMI with good accuracy, the present study is dedicated to the development and validation of an algorithm (hereafter referred to as V1SPM) to assess SPM from Rrs(λ) over inland and coastal waters of Vietnam. For that purpose, an in-situ data set of hyper-spectral Rrs(λ) and SPM (from 0.47 to 240.14 g·m−3) measurements collected at 205 coastal and inland stations has been gathered. Among the different approaches, including four historical algorithms, the polynomial algorithms involving the red-to-green reflectance ratio presents the best performance on the validation data set (mean absolute percent difference (MAPD) of 18.7%). Compared to the use of a single spectral band, the band ratio reduces the scatter around the polynomial fit, as well as the impact of imperfect atmospheric corrections. Due to the lack of matchup data points with VNREDSat-1, the full VNREDSat-1 processing chain (atmospheric correction (RED-NIR) and V1SPM), aiming at estimating SPM from the top-of-atmosphere signal, was applied to the Landsat-8/OLI match-up data points with relatively low to moderate SPM concentration (3.33–15.25 g·m−3), yielding a MAPD of 15.8%. An illustration of the use of this VNREDSat-1 processing chain during a flooding event occurring in Vietnam is provided.

scholarly journals Retrieval of Suspended Particulate Matter in Inland Waters with Widely Differing Optical Properties Using a Semi-Analytical Scheme

2019 ◽  
Vol 11 (19) ◽  
pp. 2283 ◽  
Author(s):  
Nariane Bernardo ◽  
Alisson do Carmo ◽  
Edward Park ◽  
Enner Alcântara
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Optical Model ◽  
Water Clarity ◽  
Average Error ◽  
Inland Waters ◽  
Chl A ◽  
Suspended Particulate

Suspended particulate matter (SPM) directly affects the underwater light field and, as a consequence, changes the water clarity and can reduce the primary production. Remote sensing-based bio-optical modeling can provide efficient monitoring of the spatiotemporal dynamics of SPM in inland waters. In this paper, we present a novel and robust bio-optical model to retrieve SPM concentrations for inland waters with widely differing optical properties (the Tietê River Cascade System (TRCS) in Brazil). In this system, high levels of Chl-a concentration of up to 700 mg/m3, turbidity up to 80 NTU and high CDOM absorption highly complicate the optical characteristics of the surface water, imposing an additional challenge in retrieving SPM concentration. Since Kd is not susceptible to the saturation issue encountered when using remote sensing reflectance (Rrs), we estimate SPM concentrations via Kd. Kd was derived analytically from inherent optical properties (IOPs) retrieved through a re-parameterized quasi-analytical algorithm (QAA) that yields relevant accuracy. Our model improved the estimates of the IOPs by up to 30% when compared to other existing QAAs. Our developed bio-optical model using Kd(655) was capable of describing 74% of SPM variations in the TRCS, with average error consistently lower than 30%.

Hydrological variability and suspended particulate matter in the middle river Niger bassin

2021 ◽  
Author(s):  
Moussa Boubacar Moussa ◽  
Amadou Abdourhamane Touré ◽  
Bruno Lartiges ◽  
Emma Rochelle Newall ◽  
Laurent Kergoat ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Rainy Season ◽  
Radiometric Measurements ◽  
Suspended Particulate ◽  
Major Mode ◽  
Niger River ◽  
Spm Concentration ◽  
Very High

<p>In the Sahel, climate variability and high population growth have led to changes in surface conditions that resulted in increased runoff coefficients and discharge in the major Sahelian rivers. The mid reaches of the Niger river have experienced significant increases in the Red flood, or local flood, that occurs during the rainy season between June and September, relative to Black flood, or Guinean flood that arrives in Niamey from December onwards.<br>The objective of this work was to characterize suspended particulate matter (SPM) during the Red and Black floods in the Niamey area and analyse their spatio-temporal dynamics. Two approaches are used : the first one consists of regular in-situ measurements of SPM concentration and in their physical and mineral characterization by electron microscopy; the second is based on monitoring water color by both in-situ and satellite (Sentinel 2) radiometric measurements.<br>SPM are characterized by very fine particles (with a major mode around 0.1-0.2 micrometers) mainly composed by kaolinites (iron oxides are also observed during the Red flood). This, combined with the very high levels of SPM concentration reached during the rainy season, results in very high values of reflectance in the visible end infrared bands. Radiometric measurements in the nir band by both the in-situ SKYE sensor and the Sentinel2 sensor are found to be significantly correlated to in-situ SPM, allowing efficient monitoring of SPM concentration in time and space.<br>SPM-discharge curves, reveal a complex relationship : SPM increases very rapidly at the beginning of the rainy season when soils are washed out after the long dry period, reaching a peak before the first discharge peak (Red flood). SPM continues to decrease during the second discharge peak (Black flood) from December to February, providing a distinct and unique signature. Analysis of satellite data allowed identifying the main sources of SPM and to quantify the significant contribution of the right bank river tributaries to sediments in the middle Niger river bassin. This contribution may further increase in the context of global changes (climate and anthropogenic) with important consequences on sediment transport but also on water quality and bacterial concentration which are strongly influenced by high SPM.</p>

scholarly journals Annual cycles of chlorophyll-<i>a</i>, non-algal suspended particulate matter, and turbidity observed from space and in-situ in coastal waters

Ocean Science ◽  
2011 ◽  
Vol 7 (5) ◽  
pp. 705-732 ◽  
Author(s):  
F. Gohin
Keyword(s):  
Particulate Matter ◽  
Continental Shelf ◽  
Mediterranean Sea ◽  
North Sea ◽  
Suspended Particulate Matter ◽  
Chlorophyll Concentration ◽  
Statistical Characteristics ◽  
Monitoring Networks ◽  
Suspended Particulate

Abstract. Sea surface temperature, chlorophyll, and turbidity are three variables of the coastal environment commonly measured by monitoring networks. The observation networks are often based on coastal stations, which do not provide a sufficient coverage to validate the model outputs or to be used in assimilation over the continental shelf. Conversely, the products derived from satellite reflectance generally show a decreasing quality shoreward, and an assessment of the limitation of these data is required. The annual cycle, mean, and percentile 90 of the chlorophyll concentration derived from MERIS/ESA and MODIS/NASA data processed with a dedicated algorithm have been compared to in-situ observations at twenty-six selected stations from the Mediterranean Sea to the North Sea. Keeping in mind the validation, the forcing, or the assimilation in hydrological, sediment-transport, or ecological models, the non-algal Suspended Particulate Matter (SPM) is also a parameter which is expected from the satellite imagery. However, the monitoring networks measure essentially the turbidity and a consistency between chlorophyll, representative of the phytoplankton biomass, non-algal SPM, and turbidity is required. In this study, we derive the satellite turbidity from chlorophyll and non-algal SPM with a common formula applied to in-situ or satellite observations. The distribution of the satellite-derived turbidity exhibits the same main statistical characteristics as those measured in-situ, which satisfies the first condition to monitor the long-term changes or the large-scale spatial variation over the continental shelf and along the shore. For the first time, climatologies of turbidity, so useful for mapping the environment of the benthic habitats, are proposed from space on areas as different as the southern North Sea or the western Mediterranean Sea, with validation at coastal stations.

scholarly journals The Advantages of Landsat 8-OLI-Derived Suspended Particulate Matter Maps for Monitoring the Subtidal Extension of Amazonian Coastal Mud Banks (French Guiana)

2018 ◽  
Vol 10 (11) ◽  
pp. 1733 ◽  
Author(s):  
Noelia Abascal Zorrilla ◽  
Vincent Vantrepotte ◽  
Erwan Gensac ◽  
Nicolas Huybrechts ◽  
Antoine Gardel
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
French Guiana ◽  
Landsat 8 ◽  
Migration Rates ◽  
Suspended Particulate ◽  
High Concentrations ◽  
Spm Concentration ◽  
And Migration ◽  
Comparison Of The Results

The coast of French Guiana is characterised by the northwestward migration of large mud banks alongshore and by high concentrations of suspended particulate matter (SPM) resulting from the strong influence of the Amazon River outflow. Surface OLI SPM concentration, linked to the footprint of the subtidal part of mud banks due to resuspension and migration processes, was used to develop a method to estimate the location of this footprint. A comparison of the results from this method with those obtained by locating the limit of the wave damping, which characterises muddy coasts, revealed good performance of the method based on recurring SPM values. The migration rates of the mud banks in French Guiana were calculated according to the delimitation of their subtidal parts, and showed slightly higher values (2.31 km/year) than suggested by earlier studies. In comparison with other methods, the migration rate estimated using the method proposed within the framework of this study takes into account the variability of the shape of the subtidal part for the first time. It was also shown that the mud banks existing on the coastal area of French Guiana present two different shapes. Our results clearly demonstrate the advantage of ocean colour data to describe mud banks according to their subtidal part, delimited using the assessment of SPM temporal variability.

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