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Detection of Total Phosphorus Concentrations of Turbid Inland Waters Using a Remote Sensing Method

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Abstract

Phosphorus (P) is widely known as a limiting nutrient of water eutrophication for inland freshwater ecosystems. Owing to the complexity of P chemistry, remote sensing detection of total phosphorus (TP) concentrations currently remains limited especially for optically complex turbid inland waters. To address this need, a new TP remote sensing algorithm is developed based on prior water optical classification and the use of support vector regression (SVR) machine. The in situ observed datasets, used in this study, were collected at specific times during 2009 ~ 2011, covering a total of 232 stations from eight cruises in Lakes Taihu, Chaohu, Dianchi, and Three Gorges reservoir of China. Three types of waters were first classified by using a recently developed NTD675 (Normalized Trough Depth of spectral reflectance at 675 nm) water classification method. Then, spectral regions sensitive specifically to each water type were explored and expressed via several band ratios and used for retrieval algorithm development. The established type-specific SVR algorithms yield relatively high predictive accuracies. Specifically, the mean absolute percentage errors (MAPE) produced with the independent validation samples were achieved at 32.7, 23.2, and 14.1 % for type 1, type 2, and type 3 waters, respectively. Such water type-specific SVR algorithms are more accurate for the classified waters than an aggregated SVR algorithm for the nonclassified water and also superior to commonly used statistical algorithms. Moreover, application of the developed algorithms with HJ1A/HSI image data demonstrates that the algorithms have a large potential for remote sensing estimation of TP concentrations in optically complex turbid inland waters.

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Acknowledgments

This research was supported by a National Natural Science Foundation for Young Scholars (No. 41101340) of China; a Public Science and Technology Research Funds Projects of Ocean (No. 201005030); an Open Research Fund (No. (11)key04) of the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing; an Open Research Fund (No. 2011LDE009) of the Key Laboratory of Digital Earth, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences; a Major Project of University Natural Science (No. 11KJA170003) funded by the Ministry of Education, Jiangsu Province; and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). We show our deep thanks to two anonymous reviewers providing valuable comments and suggestions.

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  1. Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

    Deyong Sun, Zhongfeng Qiu & Shaoqi Gong

  2. School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

    Deyong Sun & Zhongfeng Qiu

  3. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, Jiangsu, China

    Yunmei Li

  4. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, Jiangsu, China

    Kun Shi

  5. College of Remote Sensing, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

    Shaoqi Gong

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Sun, D., Qiu, Z., Li, Y. et al. Detection of Total Phosphorus Concentrations of Turbid Inland Waters Using a Remote Sensing Method. Water Air Soil Pollut 225, 1953 (2014). https://doi.org/10.1007/s11270-014-1953-6

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