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

Abstract

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.

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

“…The combination of several models adapted to each concentration range is the main reason for this result, together with the selection of the best-fitted models. As proved by other studies [35][36][37], the selection of a specific model combining different bands is an improvement when estimating the SPM concentration in coastal waters. Table 8 shows the in situ-satellite match-up results using different SPM models.…”

“…Again, the purpose of this study was not to provide the best SPM models for each area, but to develop a method and test it on selected satellite data recorded for optimal conditions (cloud-free, clear atmosphere) representative of a wide range of SPM concentrations in coastal and estuarine waters. Similar methods have already been developed [35,36], but the procedure presented in the present study (1) automatically selects the model switching bounds based on in situ measurements; (2) fully applies the method to real satellite data provided by three different sensors; and (3) validates the results based on match-ups with field data. …”

Fusion of Landsat-8/OLI and GOCI Data for Hourly Mapping of Suspended Particulate Matter at High Spatial Resolution: A Case Study in the Yangtze (Changjiang) Estuary

“…The RSR curves in the visible and NIR bands are shown as dashed lines in Figure 2. Although L8/OLI is not designed for ocean monitoring, its advantages of high spatial resolution and the increased number of bands, combined with its improved signal-tonoise ratio and data quality, make it increasingly used in ocean color remote sensing research and especially in estuarine and coastal research [26][27][28][29][30][31][32][33].…”

On the Potential of Robust Satellite Techniques Approach for SPM Monitoring in Coastal Waters: Implementation and Application over the Basilicata Ionian Coastal Waters Using MODIS‐Aqua

“…These high values are in contrast with those obtained by previous studies [31,42], where the use of red band proved to be suitable for the retrieval of SPMc up to~50 g/m 3 , while the use of the NIR band is more appropriate for higher SPMc values. In order to avoid such unphysical SPM concentrations achieved using only the red band, a combined approach, as previously proposed by [21], can be implemented. Red band R rs can be used for SPMc <~50 g/m 3 , while the NIR one is preferable for higher SPMc values.…”

“…Equation (2) is used for the slightly-to-moderately turbid waters (Rrs(645) ≤ 0.03 sr −1 , corresponding to SPMc < ~50 g/m³), while Equation (3) is applied for more turbid waters (Rrs(645) ≥ 0.04 sr −1 , SPMc > ~150 g/m³). SPMc corresponding to the 0.03 < Rrs < 0.04 sr −1 range is computed using a weighted average, calculating the weights by applying a logarithmic function (see [21] for more details on the methods). Keeping in mind that [10] found, as mentioned above, an error of about 30% and 40% in calibration and validation respectively, it can be speculated that such an error affects at least the absolute SPMc maps computed over BRCW.…”