Estimation of SO42- ion in saline soil using VIS-NIR spectroscopy under different human activity stress

Anhong Tian; Junsan Zhao; Chengbiao Fu; Heigang Xiong

doi:10.1016/j.saa.2022.121647

Estimation of SO₄^2- ion in saline soil using VIS-NIR spectroscopy under different human activity stress

Spectrochim Acta A Mol Biomol Spectrosc. 2022 Dec 5:282:121647. doi: 10.1016/j.saa.2022.121647. Epub 2022 Jul 22.

Authors

Anhong Tian¹, Junsan Zhao², Chengbiao Fu³, Heigang Xiong⁴

Affiliations

¹ Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650093, China; College of Information Engineering, Qujing Normal University, Qujing 655011, China.
² Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650093, China.
³ Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650093, China. Electronic address: fucb@kust.edu.cn.
⁴ College of Applied Arts and Science, Beijing Union University, Beijing 100083, China.

PMID: 35944403
DOI: 10.1016/j.saa.2022.121647

Abstract

SO₄^2- ion is an important indicator of soil salinization degree, but there are few researches on quantitative inversion of SO₄^2- content based on hyperspectral and fractional-order derivative (FOD). This study aimed to improve the prediction accuracy of SO₄^2- content in arid regions using visible and near-infrared (VIS-NIR) spectroscopy. The study area was divided into three regions according to different human activity stress, namely, lightly affected region (Region A), moderately affected region (Region B) and severely affected region (Region C). The combination estimation method of spectral transformations (R, R, 1/R, lgR, 1/lgR), FOD, significance test band (STB), and partial least squares regression (PLSR) were been constructed, and four models (FULL-PLSR, FOD-FULL-PLSR, IOD-STB-PLSR, FOD-STB-PLSR) were also used to compare and analyze the estimation accuracy. Simulation results show that the optimal prediction model of three regions is FOD-STB-PLSR, its spectral transformation is established by R, 1/R and R in Region A, B, and C, respectively. Its RPD is 2.4701, 3.4679 and 1.9781, and its optimal FOD derivative is located at 1.8-, 1.1- and 1.1-order, respectively. It means that FOD can fully extract VIS-NIR spectroscopy details, the higher-order FOD is more capable of extracting characteristic data than low-order FOD, and the predictive ability of the best estimation model is very good, extremely strong and relatively good in Region A, B and C, respectively. Compared with the best IOD-STB-PLSR of each region, the RPD of the optimal FOD-STB-PLSR model has increased more than 38%, 32%, and 19%, respectively. This study shows that the proposed FOD-STB-PLSR model is suitable for estimating the SO₄^2- ion content of saline soil under different human activity stresses, and the study can provide a certain technical reference value for the monitoring of saline soil in arid areas.

Keywords: Different human activity stress; Field hyperspectral measurement; Fractional-order derivative; SO(4)(2−) ion; Saline soil.

MeSH terms

Computer Simulation
Human Activities
Humans
Least-Squares Analysis
Soil* / chemistry
Spectroscopy, Near-Infrared* / methods

Substances

Soil