Remote Sensing Retrieval of Total Phosphorus in the Pearl River Channels Based on the GF-1 Remote Sensing Data

Shijun Lu,Ruru Deng,Yeheng Liang,Longhai Xiong,Xianjun Ai,Yan Qin

doi:10.3390/rs12091420

Abstract

Total phosphorus (TP) concentration is one of the indicators for surface water quality evaluation. In this study, an indirect algorithm was proposed to retrieve TP concentration. This algorithm retrieves the TP concentration in urban waters based on Gaofen-1 (GF-1) remote sensing data. The algorithm uses the correlation between remote-sensing reflectance, optically significant constituents of water (chlorophyll, suspended sediment, and organic matter (excluding algae)), and TP to establish a retrieval model. First, the concentrations of optically active components are retrieved using a semi-analytical model. Second, the correlation between TP and optically active components is used to retrieve the TP concentration in waters. The GF-1 remote sensing data for 7 August 2015 were used to perform remote sensing retrieval of TP concentration in the Pearl River channels in Guangzhou, China. The results show that the TP concentration in most areas of the Front Channel, Western Channel, Guangzhou Channel, and the western part of the Back Channel was higher than 0.2 mg/L, while the TP concentration in the middle and eastern parts of the Back Channel was generally lower than 0.2 mg/L. The mean absolute percentage error of the retrieval is 24.18%. The experimental results show that the model is suitable for remote sensing retrieval of TP in urban waters in Guangzhou.

Highlights

Pollution in coastal waters and inland waters has become increasingly severe
The algorithm establishes a retrieval model that is based on the relationship among remote-sensing reflectance, optically significant constituents of water, and Total phosphorus (TP)
The TP concentration of waters is retrieved by using the correlation between TP and optically active components

Summary

Introduction

Pollution in coastal waters and inland waters has become increasingly severe. Nitrogen and phosphorus nutrients that enter waters through various channels are important reasons for eutrophication [1,2,3,4]. Conventional water quality sampling and monitoring methods are time-consuming and demand large efforts and costs. Local water quality information about the monitored section can be obtained. Water quality status and changes in a large area cannot be accurately obtained. Remote sensing technology has the advantages of a broad monitoring range, fast speed, and low costs, which facilitate long-term continuous monitoring. Remote sensing technology can be used to detect problems such as pollution sources and a pollutant diffusion status, which are hardly possible by using conventional monitoring methods. Remote sensing technology is increasingly employed in water quality monitoring studies [5,6]

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