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 A Simple 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

2020 ◽  
Author(s):  
Dat Dinh Ngoc ◽  
Hubert Loisel ◽  
Vincent Vantrepotte ◽  
Huy Chu Xuan ◽  
Ngoc Nguyen Minh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Landsat 8 ◽  
Band Ratio ◽  
Data Set ◽  
Spectral Bands ◽  
Processing Chain ◽  
Suspended Particulate ◽  
Data Points

VNREDSat-1 is the first Vietnamese satellite allowing the survey of environmental parameters such as vegetation and water coverages, or surface water quality at medium spatial resolution (from 2.5 to 10 meters depending on the considered channel). The NAOMI sensor on board VNREDSat-1 has the required spectral bands to assess the suspended particulate matter concentration, SPM. Because recent studies have shown that the remote sensing reflectance, Rrs(), at the blue (450 – 520 nm), green (530 – 600 nm), and red (620 – 690 nm) spectral bands can be assessed from NAOMI with a 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() over inland and coastal waters of Vietnam. For that purpose, an in situ data set of hyper-spectral Rrs() 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 4 historical algorithms, the polynomial algorithms involving the red-to-green reflectance ratio presents the best performance on the validation data set (MAPD of 18,7%). Compared to the use of a single spectral band, the band ratio allows to reduce 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 (RED-NIR and V1SPM) aiming at estimate SPM from the top-of-atmosphere signal has been applied to the Landsat-8/OLI match-up data points with relatively low to moderate SPM concentration (3.33-15.25 g.m-3) showing 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 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 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.

scholarly journals Qualitative Dynamics of Suspended Particulate Matter in the Changjiang Estuary from Geostationary Ocean Color Images: An Empirical, Regional Modeling Approach

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4186 ◽  
Author(s):  
Dinghui Shang ◽  
Huiping Xu
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Ocean Color ◽  
Changjiang Estuary ◽  
Separate Analysis ◽  
High Concentration ◽  
The Changjiang Estuary ◽  
Band Ratio ◽  
Sea Bed ◽  
Suspended Particulate

The suspended particulate matter (SPM) in Changjiang Estuary is characterized by a high concentration of significant diurnal dynamics. With a higher temporal resolution (eight images obtained per day), Geostationary Ocean Color Imager (GOCI) was selected as the primary remote sensor for the dynamics monitoring in this paper, instead of other satellite sensor working in polar orbit. Based on the characteristics of the field spectra measured in the estuary, an empirical model was established with the band ratio of Rrs745 divided by Rrs490 and proven effective in Suspended Particulate Matter (SPM) estimation (R2 = 0.9376, RMSE = 89.32 mg/L). While, Validation results showed that the model performed better in coastal turbid waters than offshore clear waters with higher chlorophyll-a concentration, stressing the importance of partitioning SPM into its major components and doing separate analysis. The hourly observations from GOCI showed that the diurnal variation magnitudes exhibited clear regional characteristics, with a maximum in the turbidity belt near the mouth and a minimum in the offshore deeper areas. In addition, comparing the monthly averaged SPM distribution with the amount of sediment discharged into the estuary, the variation in estuarine turbidity maximum zone is more likely contributed by the sediments resuspended from the sea bed that has already accumulated in the estuarine delta.

scholarly journals Suspended Particulate Matter Concentrations Retrieved from Self-Calibrated Multispectral Satellite Imagery

2011 ◽  
Vol 59 (4) ◽  
pp. 251-261 ◽  
Author(s):  
Milan Onderka ◽  
Marek Rodný ◽  
Yvetta Velísková
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Satellite Imagery ◽  
Suspended Particulate Matter ◽  
Optical Model ◽  
Near Infrared ◽  
Remotely Sensed Data ◽  
Suspended Particulate ◽  
Multispectral Satellite Imagery ◽  
Visual Domain

Suspended Particulate Matter Concentrations Retrieved from Self-Calibrated Multispectral Satellite ImageryInland waters are known to be laden with high levels of suspended particulate matter (SPM). Remotely sensed data have been shown to provide a true synoptic view of SPM over vast areas. However, as to date, there is no universal technique that would be capable of retrieving SPM concentrations without a complete reliance on time-consuming and costly ground measurements ora prioriknowledge of inherent optical properties of water-borne constituents. The goal of this paper is to present a novel approach making use of the synergy found between the reflectance in the visual domain (~ 400-700 nm) with the near-infrared portion of the spectrum (~ 700-900 nm). The paper begins with a brief discourse of how the shape and spectral dependence of reflectance is determined by high concentrations of SPM. A modeled example is presented to mimic real-world conditions in fluvial systems, with specific absorption and scattering coefficients of the virtual optically active constituents taken from the literature. Using an optical model, we show that in the visual spectral domain (~ 400-700 nm) the water-leaving radiance responds to increasing SPM (0-100 g m-3) in a non-linear manner. Contrarily to the visual spectra, reflectance in the near infrared domain (~ 700-900 nm) appears to be almost linearly related to a broad range of SPM concentrations. To reduce the number of parameters, the reflectance function (optical model) was approximated with a previously experimentally verified exponential equation (Schiebeet al., 1992: Remote sensing of suspended sediments: the Lake Chicot, Arkansas project, Int. J. Remote Sensing,13, 8, 1487-1509). The SPM term in Schiebe's equation was expressed as a linear function of top-of-atmosphere reflectance. This made it possible to calibrate the reflectance in the visual domain by reflectance values from the near-IR portion of the spectrum. The possibility to retrieve SPM concentrations from only remote sensing data without any auxiliary ground mea-surements is tested on a Landsat ETM + scene acquired over a reservoir with moderately turbid water with SPM concentrations between 15-70 g m-3. The retrieved concentrations (on average) differ from in-situ measurement by ~ 10.5 g m-3.

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