Deriving Particulate Organic Carbon in Coastal Waters from Remote Sensing: Inter-Comparison Exercise and Development of a Maximum Band-Ratio Approach

Abstract

Recently, different algorithms have been developed to assess near-surface particulate organic matter (POC) concentration over coastal waters. In this study, we gathered an extensive in situ dataset representing various contrasted bio-optical coastal environments at low, medium, and high latitudes, with various bulk particulate matter chemical compositions (mineral-dominated, 50% of the data set, mixed, 40%, or organic-dominated, 10%). The dataset includes 606 coincident measurements of POC concentration and remote-sensing reflectance, R rs, with POC concentrations covering three orders of magnitude. Twelve existing algorithms have then been tested on this data set, and a new one was proposed. The results show that the performance of historical algorithms depends on the type of water, with an overall low performance observed for mineral-dominated waters. Furthermore, none of the tested algorithms provided satisfactory results over the whole POC range. A novel approach was thus developed based on a maximum band ratio of R rs (red/blue, red/yellow or red/green ratio). Based on the standard statistical metric for the evaluation of inverse models, the new algorithm presents the best performance. The root-mean square deviation for log-transformed data (RMSD log ) is 0.25. The mean absolute percentage difference (MAPD) is 37.48%. The mean bias (MB) and median ratio (MR) values are 0.54 µg L −1 and 1.02, respectively. This algorithm replicates quite well the distribution of in situ data. The new algorithm was also tested on a matchup dataset gathering 154 coincident MERIS (MEdium Resolution Imaging Spectrometer) R rs and in situ POC concentration sampled along the French coast. The matchup analysis showed that the performance of the new algorithm is satisfactory (RMSD log = 0.24, MAPD = 34.16%, MR = 0.92). A regional illustration of the model performance for the Louisiana continental shelf shows that monthly mean POC concentrations derived from MERIS with the new algorithm are consistent with those derived from the 2016 algorithm of Le et al. which was specifically developed for this region.3 of 29 were tested over this in situ dataset. A new empirical algorithm involving a maximum band ratio was then developed. Finally, the new approach was applied to a dataset of the medium resolution imaging spectrometer (MERIS) and a coastal region was selected, where the spatial changes of POC concentrations were discussed. Data and Methods In Situ DataThe in-situ dataset includes the concentration of biogeochemical parameters (POC, Chla, and suspended particulate matter, SPM) and remote sensing reflectance spectra R rs (λ) where λ is the wavelength. Measurements were collected by different contributors and instruments undoubtedly introducing uncertainties, which are not necessarily well characterized (Table 1). The field measurement protocols and data processing are described in detail in related papers listed in Table 1. Measurements were sampled between 1997 and 2015 in various coastal regions (Figure 1): European coastal waters ...

Absorption-based algorithm for satellite estimating the particulate organic carbon concentration in the global surface ocean

“…The BG algorithm was established using in situ POC concentrations ranging from 12 to 270 mg/m 3 , and the CI POC algorithm was established using in situ POC concentrations less than 1000 mg/ m 3 . As a result, the BG and CI POC algorithms had significant errors in coastal waters with complex optical environments (Duan et al, 2014;Evers-King et al, 2017;Le et al, 2017;Le et al, 2018;Lin et al, 2018;Jiang et al, 2019;Tran et al, 2019).…”

Estimating Organic and Inorganic Part of Suspended Solids from Sentinel 2 in Different Inland Waters

“…Several bio-optical algorithms have been created to estimate the Particulate Organic Carbon (POC) concentration in oceanic layers [66][67][68][69][70] and eutrophic lakes [71]. These algorithms were obtained for band ratios corresponding to red-to-blue (R 665 /R 490 ), red-to-green (R 665 /R 560 ), or blue-to-red (R 490 /R 665 ) for ocean studies and for blue-to-green (R 443 /R 560 and R 490 /R 560 ) ratios for lake studies.…”

Influence of Dispersed Oil on the Remote Sensing Reflectance—Field Experiment in the Baltic Sea

“…A further five ratios in Figure 10 represent blue-to-red R rs band ratios which do not have any standard global application in bio-optical algorithms in the ocean, however they are used locally in coastal waters, e.g., to derive surface concentrations of suspended particulate matter (SPM) and particulate organic carbon (POC) [71,73]. We found that there are R rs band ratios affected by all or most types of investigated oils.…”