Models of Remote Sensing Retrieval of Suspended Sediment Particle Size in the Poyang Lake Based on Measured Spectral Reflectance Data

KUANG Run-yuan; XIE Jia; ZHANG Meng; LI Wen-hong; ZHANG Gang-hua

doi:10.11988/ckyyb.20160728

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Journal of Changjiang River Scientific Research Institute ›› 2017, Vol. 34 ›› Issue (11) : 132-137. DOI: 10.11988/ckyyb.20160728

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Models of Remote Sensing Retrieval of Suspended Sediment Particle Size in the Poyang Lake Based on Measured Spectral Reflectance Data

KUANG Run-yuan, XIE Jia, ZHANG Meng, LI Wen-hong, ZHANG Gang-hua

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Abstract

Particle size of suspended sediment, as an important parameter reflecting water quality, has an influence on the spectral reflectance of water. Study of the relationship between particle size and reflectance is of great significance to water environment monitoring in inland lakes. In this paper, the suspended sediment particle size of the Poyang Lake was retrieved using different mathematical models based on correlation analysis according to measured spectral reflectance data. Results show that: 1) volume percentage median diameter is suitable for the retrieval model for turbid area; while quantity percentage median diameter is suitable for clear water; 2) in turbid area, single band Ⅳ is the sensitive wave band; whereas in clear water, single band Ⅱ and single band Ⅲ are sensitive wave bands. In addition, the reflectance ratio of band Ⅱ to band Ⅲ is the sensitive wave band in the whole study area; 3) in the retrieval model of single band reflectance, power function is suitable for the retrieval of suspended sediment particle size in the Poyang lake; while in the model of band reflectance ratio, polynomial model is the most suitable.

Key words

Poyang Lake / particle size of suspended sediment / remote sensing reflectance ratio / quantitative inversion / sensitive wave band

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KUANG Run-yuan, XIE Jia, ZHANG Meng, LI Wen-hong, ZHANG Gang-hua. Models of Remote Sensing Retrieval of Suspended Sediment Particle Size in the Poyang Lake Based on Measured Spectral Reflectance Data[J]. Journal of Changjiang River Scientific Research Institute. 2017, 34(11): 132-137 https://doi.org/10.11988/ckyyb.20160728

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