Evaluation of Unified Algorithms for Remote Sensing of Chlorophyll-a and Turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam Reservoir of South Africa under Eutrophic and Ultra-Turbid Conditions
Evaluation of Unified Algorithms for Remote Sensing of Chlorophyll-a and Turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam Reservoir of South Africa under Eutrophic and Ultra-Turbid Conditions
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DOI：
10.3390/w10050618
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发表时间：
2018-05
期刊：
影响因子：
3.4
通讯作者：
Y. Sakuno;H. Yajima;Y. Yoshioka;Shogo Sugahara;M. A. Elbasit;E. Adam;J. Chirima
中科院分区：
文献类型：
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作者：
Y. Sakuno;H. Yajima;Y. Yoshioka;Shogo Sugahara;M. A. Elbasit;E. Adam;J. Chirima
我们评估了日本真次湖和中海湖（SJNU）以及南非瓦尔大坝水库（VDR）富营养化和超浑浊水体叶绿素-a （Chla）和浑浊度的统一遥感算法。为了实现这一目标，我们使用了2016年7月至2017年3月期间在这些水域收集的38个遥感反射率（Rrs）、Chla和浊度数据集。因此，我们澄清了以下事项。作为统一的Chla模型，我们使用两波段模型（2- bm）和三波段模型（3- bm）获得了较强的相关性（R2 = 0.7, RMSE = 2 mg m−3），Rrs(687)/Rrs（672）和[Rrs−1(687)- Rrs−1(672)]× Rrs（832）。作为统一的浊度模型，我们使用2- bm和3-BM获得了较强的相关性（R2 = 0.7, RMSE = 260 NTU）， Rrs(763)/Rrs（821）和Rrs(810)−[Rrs(730) + Rrs(770)]/2。在针对Sentinel-2多光谱成像仪（MSI）频段时，我们将Chla算法的重点放在了MSI频段4和5 （Rrs（740）和Rrs(775)）上。当光学分离SJNU和VDR数据时，使用MSI波段3和4的斜率（Rrs（560）和Rrs(665)）以及MSI波段7和9的斜率（Rrs（775）和Rrs(865)）是有效的。
We evaluated unified algorithms for remote sensing of chlorophyll-a (Chla) and turbidity in eutrophic and ultra-turbid waters of Japan’s Lake Shinji and Lake Nakaumi (SJNU) and the Vaal Dam Reservoir (VDR) in South Africa. To realize this objective, we used 38 remote sensing reflectance (Rrs), Chla and turbidity datasets collected in these waters between July 2016 and March 2017. As a result, we clarified the following items. As a unified Chla model, we obtained strong correlation (R2 = 0.7, RMSE = 2 mg m−3) using a two-band model (2-BM) and three-band model (3-BM), with Rrs(687)/Rrs(672) and [Rrs−1(687) − Rrs−1(672)] × Rrs (832). As a unified turbidity model, we obtained strong correlation (R2 = 0.7, RMSE = 260 NTU) using 2-BM and 3-BM, with Rrs(763)/Rrs(821) and Rrs(810) − [Rrs(730) + Rrs(770)]/2. When targeting the Sentinel-2 Multispectral Imager (MSI) frequency band, we focused on MSI Bands 4 and 5 (Rrs(740) and Rrs(775)) for the Chla algorithm. When optically separating SJNU and VDR data, it is effective to use the slopes of MSI Bands 3 and 4 (Rrs (560) and Rrs (665)) and the slopes of MSI Bands 7 and 9 (Rrs(775) and Rrs(865)).