TY  - EJOU
AU  - Luo, Yaping 
AU  - Guo, Na 
AU  - Liu, Dong 
AU  - Peng, Shuming 
AU  - Wang, Xinchen 
AU  - Wu, Jie 

TI  - Inversion of Water Quality TN-TP Values Based on Hyperspectral Features and Model Validation
T2  - Revue Internationale de Géomatique

PY  - 2023
VL  - 32
IS  - 1
SN  - 2116-7060

AB  - Using hyperspectral data collected in January and June 2022 from the Sha River, the concentrations of total nitrogen (TN) and total phosphorus (TP) were estimated using the differential method. The results indicate that the optimal bands for estimation vary monthly due to temperature fluctuations. In the TN model, the power function model at 586 nm in January exhibited the strongest fit, yielding a fit coefficient (R<sup>2</sup>) of 0.95 and F-value of 164.57 at a significance level (<i>p</i>) of less than 0.01. Conversely, the exponential model at 477 nm in June provided the best fit, with R<sup>2</sup> = 0.93 and F = 80.95 at <i>p</i> < 0.01. In the TP model, the exponential model fit of the differential values at 851 nm with TP in January produced the best results, with R<sup>2</sup> = 0.78 and F = 20.61. However, the overall fit in June outperformed that in January. Specifically, the quadratic and linear model fits of the differential values at 824 and 863 nm with TP achieved R<sup>2</sup> = 0.96 and F-values of 34.42 and 203.34, respectively.
KW  - Water hyperspectral; seasonal variation; total phosphorus; total nitrogen; inversion estimation

DO  - 10.32604/RIG.2023.046014