Assessment of MODIS-Aqua chlorophyll-a algorithms in coastal and shelf waters of the eastern Arabian Sea

Tilstone, Gavin H.; Lotliker, Aneesh A.; Miller, Peter I.; Ashraf, P. Muhamed; Kumar, T. Srinivasa; Suresh, T.; Ragavan, B.R.; Menon, Harilal B.

doi:10.1016/j.csr.2013.06.003

Cited by 61 publications

(42 citation statements)

References 32 publications

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“…While these low magnitude values were close to the observed for our samples (ranged from 0.4 to 30.0 mg m −3 ), the large majority of chla samples (~82%) were above 1.0 mg m −3 . We also must consider that the increased concentrations of CDOM and total suspended matter in the studied waters impact the accuracy of the current blue-green ratio algorithm to retrieve chla, as demonstrated for other optically complex waters [80]. The variable concentrations of CDOM and total suspended matter play a role in the magnitude and shape of the reflectance signal and therefore the efficacy of the OC3M algorithm.…”

Section: Chlorophyll Retrievalsmentioning

confidence: 99%

Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data

et al. 2017

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Abstract:There is an increasing need for satellite-derived accurate chlorophyll-a concentration (chla) products to improve fisheries management in coastal regions. However, the methods used to derive these products have to be evaluated, so the associated uncertainties are known. The performance of three atmospheric correction methods, the near infrared (NIR), the shortwave infrared (SWIR), and the Management Unit of the North Seas Mathematical Models with an additional modification (MUMM + SWIR), and derived chla products based on the Moderate Resolution Imaging Spectroradiometer AQUA (MODIS) images acquired from 2002 to 2014 over the west coast of Canada and the United States were evaluated. The atmospherically corrected products and above-water reflectance were compared with in situ AERONET (N~650) and above-water reflectance (N~34) data, and the Ocean Color 3 MODIS (OC3M)-derived chla were compared with in situ chla measurements (N~82). The statistical analysis indicated that the MUMM + SWIR method was the most appropriate for this region, with relatively good retrievals of the atmospheric products, improved retrieval of remote sensing reflectance with bias lower than 20% for the OC3M bands, and improved retrievals of chla (r = 0.83, slope = 0.89, log RMSE = 0.33 mg m −3 for ±1 h). The poorest chla retrievals were achieved with the SWIR and NIR methods. These results represent the most comprehensive satellite data analysis of MODIS retrievals for this region and provide a framework for the MUMM + SWIR method that can be further tested in other coastal regions of the world.

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Section: Chlorophyll Retrievalsmentioning

confidence: 99%

Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data

et al. 2017

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“…South China Sea was categorized case-1 waters or oligotrophic condition. The OC3M also work well at Eastern Arabian Sea that resulted no significant difference between insitu Chlorophyll-a and OC3M with R 2 = 0.73 and RSME = 0.309 and OC3M was supperior compared with GSM (GarverSiegel-Maritorena) and GIOP (Generalized Inherent Optical Property) algorithm (Tilstone, et al, 2013). The eastern Arabian Sea coastal shelf is influenced by river run-off, winter convection and monsoon upwelling (Tilstone, et al, 2013), but this area faced derectly to Indian Ocean and seemed to be Case-1 waters.…”

Section: Match-up Analysismentioning

confidence: 92%

Modis Standard (Oc3) Chlorophyll-a Algorithm Evaluation in Indonesian Seas

Winarso¹,

Marini²

2017

IJReSES

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Abstract. The MODIS-estimated chlorophyll-a information was widely used in some operational application in Indonesia. However, there is no information about the performance of MODIS chlorophyll-a in Indonesian seas and there is no data used in development of algorithm was taken in Indonesian seas. Even the algorithm was validated in other area, it is important to know the performance of the algorithm work in Indonesian seas. Performance of MODIS Standard (OC3) algorithm at Indonesian seas was analyzed in this paper. The in-situ chlorophyll-a concentration data Satellite data which is used is Ocean Color MODIS Level-2 Product that downloaded from NASA and MODIS L-0 from LAPAN Ground Station. MODIS Level 0 from LAPAN then processed to Level-2 using latest SeaDAS Software. The match-up resulted the MNB(%) is -4.8% that means satellite-estimated was underestimate in 4.8 % and RMSE is 0.058. When the data was separated following to the data source, the correlation and trend line equation became better. From MOMSEI Cruise data, the MNB(%) was -18.8% and RMSE 0.05. From Pacific Ocean Data, MNB (%) was -27 % and RMSE 0.049. From SONNE Cruise 2005, MNB (%) was -27 % and RMSE 0.049. MODIS standard algorithm is work well in Indonesia case-1 seawaters, which contain chlorophyll-a only, and derived that influence to the electromagnetic wave.

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“…But MODIS data overestimated Chl-a in the two types of water waters and the overestimation increased lineally with the increase in Chl-a concentration. We also compared the result with previous works, the MODIS Chl-a product has been evaluated in the eastern Arabian Sea by Tilstone et al (2013), in the Antarctic, Equatorial Pacific, California Current, western midPacific, and the West Florida Shelf by Carder et al (2004), in the Argentine continental shelf and shelf-break regions by Dogliotti et al (2014), in the Celtic Sea, the Western English Channel and North Sea by Blondeau-Patissier et al (2004). These works reported that although there were no significant differences between the in-situ measured and MODIS Chl-a concentration, MODIS underestimated Chl-a in the Argentine continental shelf and at shelf-break regions, and overestimated it in the North Sea.…”

Section: Validation Of Modis Chl-a Concentrationmentioning

confidence: 99%

“…This inconsistency is due to the optically active substance in the water column. MODIS data provided biased estimation in water regions where the Inherent Optical Properties (IOP) are determined by phytoplankton and also by absorption due to colored dissolved organic material (CDOM) and scattering by Total Suspended Matter (TSM) (Prieur and Sathyendranath 1981;Sathyendranath et al 2001;Blondeau-Patissier et al 2004;Carder et al 2004;Tilstone et al 2013;Dogliotti et al 2014). Based on these works the MODIS Chl-a product is capable of analyzing the spatio-temporal variations in the Chl-a concentration in the northern SCS.…”

Section: Validation Of Modis Chl-a Concentrationmentioning

confidence: 99%

“…Satellite observed ocean color imagery has been widely used to retrieve the Chl-a concentration (Tang et al 1998;Chen et al 2004;Peñaflor et al 2007;Siegel et al 2013;Tilstone et al 2013). A variety of remote sensing data, including Coastal Zone Color Scanner (CZCS), Sea-viewing Wide Field of View Sensor (SeaWiFS), and Advanced Very High Resolution Radiometer (AVHRR), have been utilized to investigate the SCS marine biological processes and environment (Tang et al 1998(Tang et al , 1999Liu et al 2002;Tseng et al 2005;Siegel et al 2013).…”

Section: Introductionmentioning

confidence: 99%

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Surface Chlorophyll-a Concentration Spatio-Temporal Variations in the Northern South China Sea Detected Using MODIS Data

Fang¹,

Ju²,

Liu³

et al. 2015

Terr. Atmos. Ocean. Sci.

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This study examines the spatio-temporal variations in the sea-surface chlorophyll-a (Chl-a) concentration and their associated underlying driving forces in the northern South China Sea (SCS) from 2004 -2010. A stratified analysis method and the Moderate Resolution Imaging Spectroradiometer (MODIS) Chl-a product, the National Centers for Environmental Prediction (NCEP) reanalysis data, with maps of monsoon winds and current systems were used in this work. Validation indicated that the MODIS-derived Chl-a is in good agreement with in-situ measurements (R 2 = 0.815), accurate enough for analyzing the temporal-spatial variations of Chl-a in the northern SCS. The results show that the spatial heterogeneity of the Chl-a concentration was lowest in winter and increased in spring. The seasonal Chl-a concentration dynamics varied spatially and depended predominantly on the distance from the coastline. The most important factors that affect the Chl-a concentration spatial variability were identified as the monsoon, surface current and sea surface temperature (SST).

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Assessment of MODIS-Aqua chlorophyll-a algorithms in coastal and shelf waters of the eastern Arabian Sea

Cited by 61 publications

References 32 publications

Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data

Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data

Modis Standard (Oc3) Chlorophyll-a Algorithm Evaluation in Indonesian Seas

Surface Chlorophyll-a Concentration Spatio-Temporal Variations in the Northern South China Sea Detected Using MODIS Data

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