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

Remote. Sens. Pub Date : 2022-02-24 DOI:10.3390/rs14051124
J. Soriano-González, Patricia Urrego, X. Sòria-Perpinyà, E. Angelats, C. Alcaraz, J. Delegido, A. Ruiz-Verdú, Carolina Tenjo, E. Vicente, J. Moreno
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引用次数: 13

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.
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C2RCC处理器组合改善内陆和沿海水质回收的研究
Sentinel-2在监测内陆和沿海水域水质方面具有巨大潜力。然而,这些水域的大气校正具有挑战性,目前还没有标准化的方法,但不同的方法在不断发展中并存。大气校正案例2区域海岸颜色(C2RCC)处理器最近更新了C2X-COMPLEX (C2XC)。本研究是首次在伊比利亚半岛东部内陆和沿海水域,与C2RCC和C2X相比,探讨其在反演水面反射率、估算叶绿素a ([Chl-a])、总悬浮物([TSM])和Secchi盘深度(ZSD)方面的性能。C2RCC处理器的原位ZSD和Kd_z90max产品之间的关系(即,90%的离开水辐照度来源于水柱的深度)证明了该产品在估计水的清晰度方面的潜力(r > 0.75)。然而,使用默认校准因子的不同处理器导出的[TSM]和[Chl-a]不适合目标场景,需要根据光学水类型重新校准或转向动态算法混合方法。这将受益于C2RCC和C2XC之间的切换,这将改善表面反射率估算的潜力扩展到更广泛的场景,并表明C2-Nets在水质运行监测方面的前景广阔。
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