Chromophoric Dissolved Organic Matter and Dissolved Organic Carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: Case Study for the Northern Gulf of Mexico

Tehrani, N. Chaichi; D’Sa, Eurico J.; Osburn, Christopher L.; Bianchi, Thomas S.; Schaeffer, Blake A.

doi:10.3390/rs5031439

Cited by 76 publications

(29 citation statements)

References 58 publications

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“…Its light absorption coefficient decays almost exponentially, from high absorption coefficients in the ultra-violet to close to zero towards red spectral range [5,6]. A strong near-linear negative correlation between CDOM absorption and salinity has been observed in most shelf sea studies [7,8].…”

Section: Introductionmentioning

confidence: 93%

“…It is presumed that perceived color of seawater in the NWES is strongly driven by CDOM and SPM although chl-a plays a seasonal and local role for example in the Central North Sea [32][33][34][35]. In situ station (blue dots) sampling was done in the German Bight (1)(2)(3)(4)(5)(6)(7)(8), North Sea (9-26), Inner Seas (27)(28)(29)(30)(31)(32)(33)(34), Irish Sea (35)(36)(37)(38)(39)(40)(41)(42)(43), and Celtic Sea (44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58)(59)(60). Region naming is based on maps from The Germany Federal Maritime and Hydrographic Agency [34] and International Hydrographic Organization [35].…”

Section: Study Areamentioning

confidence: 99%

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Physical, Bio-Optical State and Correlations in North–Western European Shelf Seas

2014

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Abstract:Color of seawater has become an integral tool in understanding surface marine ecosystems and processes. In this paper we seek to assess the correlations and consequently the potential of using shipborne remote sensing products to infer marine environmental parameters. Typical seawater parameters are chlorophyll-a (chl-a), colored dissolved organic material (CDOM), suspended particulate material (SPM), Secchi-disk depth (SDD), temperature, and salinity. These parameters and radiometric quantities were observed from a total of 60 stations covering German Bight, North Sea, Inner Seas, Irish Sea, and Celtic Sea. Bio-optical models developed in this study were used to predict the in situ measured parameters, with low mean unbiased percent differences and absolute percent difference less than 35%. Our investigations show that the use of ocean color products namely the Forel-Ule Index to infer seawater parameters is encouraging. The constrained spatial and temporal span of measured in situ parameters does limit the accuracy of our models. Absorption coefficients of the main color producing agents CDOM, chl-a, and inorganic fraction of SPM (iSPM) were determined to estimate absorption budgets. During the field campaign, iSPM was the primary light absorber over the spectral range (400-700 nm) although variabilities were observed in the regional seas.

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Section: Introductionmentioning

confidence: 93%

Section: Study Areamentioning

confidence: 99%

Physical, Bio-Optical State and Correlations in North–Western European Shelf Seas

2014

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“…The response is always associated with extreme wave heights, large current velocities, and substantial water level variations (Allahdadi et al [1]). Furthermore, tropical cyclones substantially contribute to transport of sediments and biogeochemical substances over oceanic and shelf waters (D'Sa et al [2]; Tehrani et al [3]; Chiaichtehrani [4]). Wave characteristics are among the most relevant oceanic responses of these storms, due to their destructive effects on structures and coastal communities as well as their substantial effects on transport phenomena in the shelf waters.…”

mentioning

confidence: 99%

Wave Spectral Patterns during a Historical Cyclone: A Numerical Model for Cyclone Gonu in the Northern Oman Sea

Allahdadi¹,

Chaichitehrani²,

Allahyar³

et al. 2017

OJFD

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The third generation wind-wave model Mike21-SW was used to study spectral characteristics of waves generated by the historical Cyclone Gonu in June 2007 along and off the Iranian coasts on the northern Oman Sea. The model was forced with the cyclone wind field generated using a Holland (1980) model based on cyclone data obtained from the Joint Typhon Warning Center (JTWC). The wave model was calibrated for the northern Oman Sea using bulk and spectral wave data at a station out of the Chabahar Bay. Evolution of directional-frequency spectra during the cyclone was investigated for two locations near the entrance and off the Chabahar Bay. At the offshore station, energy was contributed to the spectrum over an approximately 180 degree directional span that included different local and remotely generated waves. As the cyclone proceeded northwestward, all spectral directions continuously rotated in the clockwise direction at both locations. Frequency spectra at these locations were investigated for four different times corresponding to different locations of Cyclone's eye and were justified using the sea growth parameter of the Joint North Sea Wave Project (JONSWAP) experiment. Using the modified JONSWAP parameters for hurricane conditions resulted in a frequency spectrum consistent with simulation results.

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“…In 2009 this procedure was not available at the laboratories which performed the water sample analysis. Many studies have reported a correlation greater than 0.9 between CDOM and DOC for marine systems [46][47][48][49]. For freshwaters, good correlation between CDOM and DOC was found by [50][51][52][53][54]; however, on the other hand, some studies reported a weaker relationship [55][56][57].…”

Section: Linking the Chemical And Optical Properties Of The Sampled Wmentioning

confidence: 93%

Applying Spectral Unmixing to Determine Surface Water Parameters in a Mining Environment

Kopačková

Hladíková

2014

Remote Sensing

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Compared to natural waters, mine waters represent an extreme water type that is frequently heavily polluted. Although they have been traditionally monitored by in situ measurements of point samples taken at regular intervals, the emergence of a new generation of multispectral and hyperspectral (HS) sensors means that image spectroscopy has the potential to become a modern method for monitoring polluted surface waters. This paper describes an approach employing linear Spectral Unmixing (LSU) for analysis of hyperspectral image data to map the relative abundances of mine water components (dissolved Fe-Fediss, dissolved organic carbon-DOC, undissolved particles). The ground truth data (8 monitored ponds) were used to validate the results of spectral mapping. The same approach applied to HS data was tested using the image data resampled to WorldView2 (WV2) spectral resolution. A key aspect of the image data processing was to define the proper pure image end members for the fundamental water types. The highest correlations detected between the studied water parameters and the fractional images using the HyMap and the resampled WV2 data, respectively, were: dissolved Fe (R 2 = 0.74 and R 2 vw2 = 0.6), undissolved particles (R 2 = 0.57 and R 2 vw2 = 0.49) and DOC (R 2 = 0.42 and R 2 vw2 < 0.40). These fractional images were further classified to create semi-quantitative maps. In conclusion, the classification still benefited from the higher spectral resolution of the HyMap data; however the WV2 reflectance data can be suitable for mapping specific inherent optical properties (SIOPs), which significantly differ from one another from an optical point of view OPEN ACCESSRemote Sens. 2014, 6 11205 (e.g., mineral suspension, dissolved Fe and phytoplankton), but it seems difficult to differentiate among diverse suspension particles, especially when the waters have more complex properties (e.g., mineral particles, DOC together with tripton or other particles, etc.).

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Chromophoric Dissolved Organic Matter and Dissolved Organic Carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: Case Study for the Northern Gulf of Mexico

Cited by 76 publications

References 58 publications

Physical, Bio-Optical State and Correlations in North–Western European Shelf Seas

Physical, Bio-Optical State and Correlations in North–Western European Shelf Seas

Wave Spectral Patterns during a Historical Cyclone: A Numerical Model for Cyclone Gonu in the Northern Oman Sea

Applying Spectral Unmixing to Determine Surface Water Parameters in a Mining Environment

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