Inversion ofWater Quality TN-TP Values Based on Hyperspectral Features andModel Validation

doi:10.32604/rig.2023.046014

	Inversion ofWater Quality TN-TP Values Based on Hyperspectral Features andModel Validation
	Luo, Yaping 1; Guo, Na1 ; Liu, Dong 2; Peng, Shuming 3; Wang, Xinchen4 ; Wu, Jie3
	2023
发表期刊	REVUE INTERNATIONALE DE GEOMATIQUE
卷号	32 期号:1 页码:38-51
摘要	Using hyperspectral data collected in January and June 2022 fromthe Sha River, the concentrations of total nitrogen (TN) and total phosphorus (TP) were estimated using the differentialmethod. 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-2) of 0.95 and F-value of 164.57 at a significance level (p) of less than 0.01. Conversely, the exponential model at 477 nm in June provided the best fit, with R-2 = 0.93 and F = 80.95 at p < 0.01. In the TP model, the exponential model fit of the differential values at 851 nmwith TP in January produced the best results, with R-2 = 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-2 = 0.96 and F-values of 34.42 and 203.34, respectively.
关键词	Water hyperspectral WATER-QUALITY seasonal variation LAKE TAIHU total phosphorus NUTRIENT total nitrogen RETRIEVAL inversion estimation
DOI	10.32604/rig.2023.046014
收录类别	ESCI
ISSN	1260-5875
语种	英语
WOS研究方向	Remote Sensing
WOS类目	Remote Sensing
WOS记录号	WOS:001148863500002
出版者	TECH SCIENCE PRESS
原始文献类型	Article
EISSN	2116-7060
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/35670
专题	工商管理学院信息工程与人工智能学院
通讯作者	Guo, Na
作者单位	1.Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Peoples R China; 2.Chengdu Univ Technol, Coll Management Sci, Chengdu 610059, Peoples R China; 3.Chengdu Univ Technol, Coll Ecol & Environm, Chengdu 610059, Peoples R China; 4.Lanzhou Univ Finance & Econ, Sch Informat Engn & Artificial Intelligence, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Luo, Yaping,Guo, Na,Liu, Dong,et al. Inversion ofWater Quality TN-TP Values Based on Hyperspectral Features andModel Validation[J]. REVUE INTERNATIONALE DE GEOMATIQUE,2023,32(1):38-51.
APA	Luo, Yaping,Guo, Na,Liu, Dong,Peng, Shuming,Wang, Xinchen,&Wu, Jie.(2023).Inversion ofWater Quality TN-TP Values Based on Hyperspectral Features andModel Validation.REVUE INTERNATIONALE DE GEOMATIQUE,32(1),38-51.
MLA	Luo, Yaping,et al."Inversion ofWater Quality TN-TP Values Based on Hyperspectral Features andModel Validation".REVUE INTERNATIONALE DE GEOMATIQUE 32.1(2023):38-51.