The development of a new optical total suspended matter algorithm for the Chesapeake Bay

Ondrusek, Michael; Stengel, E.; Kinkade, Christopher S.; Vogel, Ronald L.; Keegstra, Phillip; Hunter, Craig N.; Kim, Chunai.

doi:10.1016/j.rse.2011.12.018

Cited by 96 publications

(89 citation statements)

References 41 publications

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“…First, a variety of empirical formulations diversely based on different spectral band combinations have been developed within different coastal sites. Single band formulations based on various spectral inputs have been, for instance, widely documented [4,[11][12][13][14][15][16][17][18]. The major issue related to these straightforward models is related to their frequent saturation in the most turbid waters due to the asymptotical shape of the link between the marine reflectance signal at a defined wavelength and SPM concentration.…”

Section: Introductionmentioning

confidence: 99%

Development of a Semi-Analytical Algorithm for the Retrieval of Suspended Particulate Matter from Remote Sensing over Clear to Very Turbid Waters

et al. 2016

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Remote sensing of suspended particulate matter, SPM, from space has long been used to assess its spatio-temporal variability in various coastal areas. The associated algorithms were generally site specific or developed over a relatively narrow range of concentration, which make them inappropriate for global applications (or at least over broad SPM range). In the frame of the GlobCoast project, a large in situ data set of SPM and remote sensing reflectance, R rs (λ), has been built gathering together measurements from various coastal areas around Europe, French Guiana, North Canada, Vietnam, and China. This data set covers various contrasting coastal environments diversely affected by different biogeochemical and physical processes such as sediment resuspension, phytoplankton bloom events, and rivers discharges (Amazon, Mekong, Yellow river, MacKenzie, etc.). The SPM concentration spans about four orders of magnitude, from 0.15 to 2626 g¨m´3. Different empirical and semi-analytical approaches developed to assess SPM from R rs (λ) were tested over this in situ data set. As none of them provides satisfactory results over the whole SPM range, a generic semi-analytical approach has been developed. This algorithm is based on two standard semi-analytical equations calibrated for low-to-medium and highly turbid waters, respectively. A mixing law has also been developed for intermediate environments. Sources of uncertainties in SPM retrieval such as the bio-optical variability, atmospheric correction errors, and spectral bandwidth have been evaluated. The coefficients involved in these different algorithms have been calculated for ocean color (SeaWiFS, MODIS-A/T, MERIS/OLCI, VIIRS) and high spatial resolution (LandSat8-OLI, and Sentinel2-MSI) sensors. The performance of the proposed algorithm varies only slightly from one sensor to another demonstrating the great potential applicability of the proposed approach over global and contrasting coastal waters.

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Section: Introductionmentioning

confidence: 99%

Development of a Semi-Analytical Algorithm for the Retrieval of Suspended Particulate Matter from Remote Sensing over Clear to Very Turbid Waters

et al. 2016

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“…Miller and Mckee 2004;Doxaran et al 2009;Petus et al 2010;Ondrusek et al., 2012). Radiance or reflectance values measured in the band 1 have been used as qualitative proxy for amounts of total suspended matter (TSM) (e.g.…”

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confidence: 99%

Monitoring spatio-temporal variability of the Adour River turbid plume (Bay of Biscay, France) with MODIS 250-m imagery

Petus

Marieu

Novoa

et al. 2014

Continental Shelf Research

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. AbstractIncreased loads of land-based pollutants through river plumes are a major threat to the coastal water quality, ecosystems and sanitary heath. Identifying the coastal areas impacted by potentially polluted freshwaters is necessary to inform management policies and prevent degradation of the coastal environment. This study presents the first monitoring of the Adour River turbid plume (south-eastern Bay of Biscay, France) using multi-annual MODIS data Satellite data are processed using a regional algorithm that allows quantifying and mapping suspended matter in coastal waters. The results are used to investigate the spatial and temporal variability of the Adour River turbid plume and to identify the risk of exposure of coastal ecosystems to the turbid plume waters. Changes in river plume orientation and extent as well as suspended matter concentration rates discharged through the river are correlated to the main hydro-climatic forcings acting in the south-eastern Bay of Biscay. The Adour River turbid plume is shown to be a highly reactive system mainly controlled by the river discharge rates and modulated by the wind changes. Despite the relatively small size of the Adour River, the Adour River turbid plume can have a non-negligible impact on the water quality of the southern Bay of Biscay and the MSM and associated contaminant/nutrients transported within the Adour turbid river plume have the potential to be disseminated far away along the northern shoreline or offshore. The main areas of influence of the river plume are defined over multi-annual (3 years) and seasonal periods. The results presented in this study show the potential of 250-m MODIS images to monitor small river plumes systems and support management and assessment of the water quality in the south-eastern Bay of Biscay.Key words: water quality, River plume, MODIS-Aqua; mineral suspended matters, spatiotemporal variability, Adour estuary. IntroductionAssessment of water quality has become a major issue worldwide and is illustrated in Europe by the implementation of the Water Framework, the Quality of Bathing Waters and the (MSFD, 2008/56/EC), respectively. These directives mainly focus on preventing the degradation of aquatic ecosystems due to anthropogenic pressures. The evaluation of the water quality status is based on the measurement of relevant water quality parameters. Among biological parameters are the composition, abundance and biomass of phytoplankton, the frequency and intensity of blooms and their influences on the water turbidity , Ferreira et al., 2011. Phy...

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“…For the two optical sensors considered here the empirical algorithms from MODIS (MOD-E) and Landsat (LAN-E) will be collectively known as empirical algorithms unless otherwise stated explicitly. The form of the equations used in the empirical methods ranged from simple linear [17,26,57,58], exponential [9,21,34,59], power [10,46,60] and other polynomial relationships [61][62][63] using single, multiple or combinations of different bands in band ratio or self-formulated indexes. To differentiate the algorithms within each sensor, algorithms will be labeled with a respective number following each sensor's name, MOD-A1 and MOD-E1 will represent MODIS semi-analytic algorithm 1 and MODIS empirical algorithm 1 respectively; likewise, a similar naming convention is followed for TSS algorithms for Landsat-based sensors.…”

Section: Tss Modelsmentioning

confidence: 99%

A Quantitative Comparison of Total Suspended Sediment Algorithms: A Case Study of the Last Decade for MODIS and Landsat-Based Sensors

Dorji

Fearns

2016

Remote Sensing

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A quantitative comparative study was performed to assess the relative applicability of Total Suspended Solids (TSS) models published in the last decade for the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat-based sensors. The quantitative comparison was performed using a suite of statistical tests and HydroLight simulated data for waters ranging from clear open ocean case-1 to turbid coastal case-2 waters. The quantitative comparison shows that there are clearly some high performing TSS models that can potentially be applied in mapping TSS concentration for regions of uncertain water type. The highest performing TSS models tested were robust enough to retrieve TSS from different water types with Mean Absolute Relative Errors (MARE) of 69.96%-481.82% for HydroLight simulated data. The models were also compared in regional waters of northern Western Australia where the highest performing TSS models yielded a MARE in the range of 43.11%-102.59%. The range of Smallest Relative Error (SRE) and Largest Relative Error (LRE) between the highest and the lowest performing TSS models spanned three orders of magnitude, suggesting users must be cautious in selecting appropriate models for unknown water types.

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The development of a new optical total suspended matter algorithm for the Chesapeake Bay

Cited by 96 publications

References 41 publications

Development of a Semi-Analytical Algorithm for the Retrieval of Suspended Particulate Matter from Remote Sensing over Clear to Very Turbid Waters

Development of a Semi-Analytical Algorithm for the Retrieval of Suspended Particulate Matter from Remote Sensing over Clear to Very Turbid Waters

Monitoring spatio-temporal variability of the Adour River turbid plume (Bay of Biscay, France) with MODIS 250-m imagery

A Quantitative Comparison of Total Suspended Sediment Algorithms: A Case Study of the Last Decade for MODIS and Landsat-Based Sensors

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