Water transparency inversion and influence factor analysis of Qiandao Lake based on Random Forest and GF-5 data

Qing Xu; Chenyi Pan; Dongchen Huang; Zepeng Jin

doi:10.1117/12.2659347

22 November 2022 Water transparency inversion and influence factor analysis of Qiandao Lake based on Random Forest and GF-5 data

Qing Xu, Chenyi Pan, Dongchen Huang, Zepeng Jin

Author Affiliations +

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 124750L (2022) https://doi.org/10.1117/12.2659347
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

Transparency is an important parameter to describe the optical properties of lake water. Based on the field measured data of April 19, 2018 and September 8, 2019, and GF-5 hyperspectral satellite images, Random Forest and BPNN methods were used to retrieve the transparency of water bodies. The study shows that the Random Forest algorithm performs well in the waters of Qiandao Lake, the R2 between the inversion value and the measured value is 0.8651, and the MAPE is 0.16m. Based on the GF-5 hyperspectral satellite image on September 8, 2019, the spatial distribution characteristics of water transparency in Qiandao Lake were obtained by using Random Forest algorithm. The results show that the overall transparency of Qiandao Lake is higher (1.3~6.8m), and the water transparency in the middle of the lake is higher than that in the northwest and southwest tributaries. According to the analysis of the measured water transparency and the environmental factors of synchronous measurement, the water transparency of Qiandao Lake is affected by many environmental factors, among which the correlation with the concentration of suspended solids is strong, and the correlation coefficient is 0.831. The correlation with total phosphorus concentration, water surface temperature, ph value, wind speed and other environmental factors is weak.

Citation Download Citation

Qing Xu, Chenyi Pan, Dongchen Huang, and Zepeng Jin "Water transparency inversion and influence factor analysis of Qiandao Lake based on Random Forest and GF-5 data", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 124750L (22 November 2022); https://doi.org/10.1117/12.2659347

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KEYWORDS

Transparency

Water

Data modeling

Remote sensing

Statistical modeling

Environmental sensing

Reflectivity

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