Towards the Combination of C2RCC Processors for Improving Water Quality Retrieval in Inland and Coastal Areas

Abstract

Sentinel-2 offers great potential for monitoring water quality in inland and coastal waters. However, atmospheric correction in these waters is challenging, and there is no standardized approach yet, but different methods coexist under constant development. The atmospheric correction Case 2 Regional Coast Colour (C2RCC) processor has been recently updated with the C2X-COMPLEX (C2XC). This study is one of the first attempts at exploring its performance, in comparison with C2RCC and C2X, in inland and coastal waters in the east of the Iberian Peninsula, in retrieving water surface reflectance and estimating chlorophyll-a ([Chl-a]), total suspended matter ([TSM]), and Secchi disk depth (ZSD). The relationship between in situ ZSD and Kd_z90max product (i.e., the depth of the water column from which 90% of the water-leaving irradiance is derived) of the C2RCC processors demonstrated the potential of this product for estimating water clarity (r > 0.75). However, [TSM] and [Chl-a] derived from the different processors with default calibration factors were not suitable within the targeted scenarios, requiring recalibration based on optical water types or a shift to dynamic algorithm blending approaches. This would benefit from switching between C2RCC and C2XC, which extends the potential for improving surface reflectance estimates to a wide range of scenarios and suggests a promising future for C2-Nets in operational monitoring of water quality.

Meta-Analysis of Satellite Observations for United Nations Sustainable Development Goals: Exploring the Potential of Machine Learning for Water Quality Monitoring

“…The use of NNs in satellite-based water quality monitoring goes beyond predictive modeling, demonstrating the algorithm's broad technical appeal. For instance, New Neural Network version.1 (NNv1) and New Neural Network version.2 (NNv2) have been used specifically to develop neural network-based algorithms such as C2RCC, multilayer neural networks (MLNNs), and Case2extreme or Case2complex (C2X) [180,253,[280][281][282][283][284][285][286][287][288][289][290]. These algorithms correct and retrieve water reflectances as well as water inherent optical properties (IOPs).…”

Semi-Automated Production and Filtering of Satellite Derived Water Quality Parameters

“…However, the performance of the processors varies depending on the scenario (sun and observation geometry, atmospheric, optical, and site-specific conditions), and there is currently no standardized approach; however, atmospheric correction processors continue to evolve as new methods and data become available. This brings the need to continue to test various atmospheric correction procedures as well as water quality retrieval methods using in situ data that accounts for a wide range of water types and environmental circumstances (Soriano-González et al, 2022;Spyrakos et al, 2018).…”

“…C2RCC processor for atmospheric correction has been updated: the current C2RCC is a modified version of the original Case 2 Regional Processor, which has been adapted to many multispectral satellites (e.g., Sentinel-2, Sentinel-3, Landsat-8). Now the C2RCC is composed by a set of three processors (i.e., C2-Nets: C2RCC, C2X, and C2X-COMPLEX) (Soriano-González et al, 2022).…”

Using C2X to Explore the Uncertainty of In Situ Chlorophyll-a and Improve the Accuracy of Inversion Models

“…The processor is categorized into Case 2 (C2), Case2eXtreme (C2X), and Case2eXtreme-complex (C2X-complex) to cater to different multispectral satellites and regions. Among these methods, the C2X processor is found to be more suitable for turbid and optically complex inland lakes [17]. The final products obtained consist of a variety of data covering remote sensing reflectance at different wavelengths, kd_z90max product, conc_chl product, and suspended matter concentration.…”

“…Carsten et al [16] confirmed the effectiveness of C2RCC in some water bodies. Jesús Soriano-González et al [17] explored the performance of C2RCC in inland waters of the Eastern Iberian Peninsula using Sentinel-2 multispectral images, which showed that C2RCC had an excellent application effect in water quality monitoring. The C2RCC has the potential to revolutionize the field of water quality remote sensing by offering exceptionally accurate and precise data regarding water quality parameters.…”