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 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 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 Preliminary analysis of variability in concentration of fine particulate matter - PM1.0, PM2.5 and PM10 in area of Poznań city

2018 ◽  
Vol 28 ◽  
pp. 01005
Author(s):  
Izabela Sówka ◽  
Anna Chlebowska-Styś ◽  
Barbara Mathews
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Preliminary Analysis ◽  
Human Life ◽  
Fine Particulate Matter ◽  
Winter Season ◽  
Correlation Coefficients ◽  
Suspended Particulate Matter Concentration ◽  
High Concentration ◽  
Suspended Particulate

It is commonly known, that suspended particulate matter pose a threat to human life and health, negatively influence the flora, climate and also materials. Especially dangerous is the presence of high concentration of particulate matter in the area of cities, where density of population is high. The research aimed at determining the variability of suspended particulate matter concentration (PM1.0, PM2.5 and PM10) in two different thermal seasons, in the area of Poznań city. As a part of carried out work we analyzed the variability of concentrations and also performed a preliminary analysis of their correlation. Measured concentrations of particulate matter were contained within following ranges: PM10 – 8.7-69.6 μg/m3, PM2.5 – 2.2-88.5 μg/m3, PM1.0 – 2.5-22.9 μg/m3 in the winter season and 1.0-42.8 μg/m3 (PM10), 1.2-40.3 μg/m3 (PM2.5) and 2.7-10.4 (PM1.0) in the summer season. Preliminary correlative analysis indicated interdependence between the temperature of air, the speed of wind and concentration of particulate matter in selected measurement points. The values of correlation coefficients between the air temperature, speed of wind and concentrations of particulate matter were respectively equal to: for PM10: -0.59 and -0.55 (Jana Pawła II Street), -0.53 and -0.53 (Szymanowskiego Street), for PM2.5: -0.60 and -0.53 (Jana Pawła II Street) and for PM1.0 -0.40 and -0.59 (Jana Pawła II Street).

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