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Open AccessArticle

Estimation of Soil Salt and Ion Contents Based on Hyperspectral Remote Sensing Data: A Case Study of Baidunzi Basin, China

1
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
2
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100049, China
3
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
4
State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating, Gansu Desert Control Desert Research Institute, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Academic Editors: Nicolo Colomabni and Thomas Meixner
Water 2021, 13(4), 559; https://doi.org/10.3390/w13040559
Received: 23 December 2020 / Revised: 17 February 2021 / Accepted: 18 February 2021 / Published: 22 February 2021
(This article belongs to the Special Issue Salinization of Water Resources: Ongoing and Future Trends)
Soil salinity due to irrigation diversion affects regional agriculture, and the development of soil composition estimation models for the dynamic monitoring of regional salinity is important for salinity control. In this study, we evaluated the performance of hyperspectral data measured using an analytical spectral device (ASD) field spec standard-res hand-held spectrometer and satellite sensor visible shortwave infrared advanced hyperspectral imager (AHSI) in estimating the soil salt content (SSC). First derivative analysis (FDA) and principal component analysis (PCA) were applied to the data using the raw spectra (RS) to select the best model input data. We tested the ability of these three groups of data as input data for partial least squares regression (PLSR), principal component regression (PCR), and multiple linear regression (MLR). Finally, an estimation model of the SSC, Na+, Cl, and SO42− contents was established using the best input data and modeling method, and a spatial distribution map of the soil composition content was drawn. The results show that the soil spectra obtained from the satellite hyperspectral data (AHSI) and laboratory spectral data (ASD) were consistent when the SSC was low, and as the SSC increased, the spectral curves of the ASD data showed little change in the curve characteristics, while the AHSI data showed more pronounced features, and this change was manifested in the AHSI images as darker pixels with a lower SSC and brighter pixels with a higher SSC. The AHSI data demonstrated a strong response to the change in SSC; therefore, the AHSI data had a greater advantage compared with the ASD data in estimating the soil salt content. In the modeling process, RS performed the best in estimating the SSC and Na+ content, with the R2 reaching 0.79 and 0.58, respectively, and obtaining low root mean squared error (RMSE) values. FDA and PCA performed the best in estimating Cl and SO42−, while MLR outperformed PLSR and PCR in estimating the content of the soil components in the region. In addition, the hyperspectral camera data used in this study were very cost-effective and can potentially be used for the evaluation of soil salinization with a wide range and high accuracy, thus reducing the errors associated with the collection of individual samples using hand-held hyperspectral instruments. View Full-Text
Keywords: soil salinization; remote sensing; numerical modelling; digital soil mapping; arid regions soil salinization; remote sensing; numerical modelling; digital soil mapping; arid regions
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MDPI and ACS Style

Wang, L.; Zhang, B.; Shen, Q.; Yao, Y.; Zhang, S.; Wei, H.; Yao, R.; Zhang, Y. Estimation of Soil Salt and Ion Contents Based on Hyperspectral Remote Sensing Data: A Case Study of Baidunzi Basin, China. Water 2021, 13, 559. https://doi.org/10.3390/w13040559

AMA Style

Wang L, Zhang B, Shen Q, Yao Y, Zhang S, Wei H, Yao R, Zhang Y. Estimation of Soil Salt and Ion Contents Based on Hyperspectral Remote Sensing Data: A Case Study of Baidunzi Basin, China. Water. 2021; 13(4):559. https://doi.org/10.3390/w13040559

Chicago/Turabian Style

Wang, Libing; Zhang, Bo; Shen, Qian; Yao, Yue; Zhang, Shengyin; Wei, Huaidong; Yao, Rongpeng; Zhang, Yaowen. 2021. "Estimation of Soil Salt and Ion Contents Based on Hyperspectral Remote Sensing Data: A Case Study of Baidunzi Basin, China" Water 13, no. 4: 559. https://doi.org/10.3390/w13040559

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