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Remote sensing estimation method of organic suspended matter concentration in inland lakes based on Sentinel-3 OLCI data

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China

  • Email：836518499@qq.com
  • Introduction：仲苏珂，1997年生，女，硕士研究生，研究方向为内陆湖泊定量遥感。E-mail： 836518499@qq.com
ZHONG Suke1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China

    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China

    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China

  • Email：heng.lyu@gmail.com
  • Introduction：吕恒，1977年生，男，教授，研究方向为水环境遥感。E-mail： heng.lyu@gmail.com
LYU Heng123*,  
  • Affiliation：

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China

YANG Ziqian1,  
  • Affiliation：

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China

LI Yangyang1,  
  • Affiliation：

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China

XU Jiafeng1,  
  • Affiliation：

    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China

MIAO Song1

Resümee

Organic Suspended Matter (OSM) is an important component of lake organic carbon pool, which is important to the study of lake ecological environment and primary productivity. At present, the research of OSM in water mainly focuses on its source composition, migration and transformation, and flux into the sea. Therefore, constructing a new method for estimating OSM in inland water is urgently needed. This method can obtain the spatial and temporal distribution characteristics of OSM concentration in the whole lake and even the whole region.In this study, the combined Taihu, Chaohu, Geui, Xiaoxingkai, Dianchi, Hongze, Hulun, and Nanyi lakes are selected as the research area, and a remote sensing method for estimating the concentration of organic suspended solids in inland water is developed. According to the slope of B6 and B7 bands and the slope of B10 and B11 bands, the water body is divided into two types, namely, the Type A water dominated by inorganic suspended matter and the Type B water dominated by OSM. On this basis, remote sensing estimation models of OSM concentration for different types of water bodies are established. The remote sensing estimation model of OSM concentration for Type A water is OSM=32.75·B17/B3-1.3537, and the remote sensing estimation model of OSM concentration for Type B water is: OSM=43.098+15.751·B10/Bl1. The band ratio B17/B3 can be used to estimate the OSM concentration of Type A water, and the band ratio B11/B10 can be used to estimate the OSM concentration of Type B water. The proposed method obtained RMSE of 5.38 mg/L and MAPE of 28.93%, which were decreased by 11.10 mg/L and 41.66%, respectively, compared with those of the traditional nonclassified OSM estimation empirical method.An empirical algorithm for retrieving OSM concentration in inland lakes is proposed on the basis of the band characteristics of Sentinel 3A-OLCI image. According to the spectral characteristics of inland water bodies, which are the slope of OLCI band B6 and B7 and the slope of band B10 and B11, the algorithm, which uses the strategy of first classification and then retrieval, can divide the water into two types: the water dominated by inorganic suspended matter and the water dominated by OSM. The OSM concentration of the water dominated by inorganic suspended matter can be estimated by using OLCI bands B3 and B17, while the OSM concentration of the water dominated by organic suspended solids can be estimated by using OLCI bands B10 and B11. Independent validation datasets show that the RMSE and MAPE estimated by this method are 5.38 mg/L and 28.93%, respectively. The estimation accuracy of this method is significantly improved compared with those of the existing retrieval algorithms for the concentration of OSM in inland water. This method has been successfully applied to obtain the temporal and spatial distribution characteristics of the OSM concentration in Taihu and Chaohu lakes in China. The method constructed in this study provides a new algorithm with higher accuracy for obtaining the OSM concentration of inland water at regional scale.The classification method of this study and the construction of the retrieval algorithm are based on several typical lakes on the basis of field sampling. However, the robustness of the algorithm still needs further examination, especially when it is applied to water with different biological optical characteristics from sampling lake. The performance of the algorithm also should be tested using a great number of field measured datasets. In future studies, the performance of the algorithm will be further tested by collecting more lake field data.

Schlüsselwort

inland water;organic suspended matter;OLCI;optical classification;quantitative estimation;empirical algorithm

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