The Link between Surface Visible Light Spectral Features and Water–Salt Transfer in Saline Soils—Investigation Based on Soil Column Laboratory Experiments

Monitoring soil salinity with remote sensing is difficult, but knowing the link between saline soil surface spectra, soil water, and salt transport processes might help in modeling for soil salinity monitoring. In this study, we used an indoor soil column experiment, an unmanned aerial vehicle multispectral sensor camera, and a soil moisture sensor to study the water and salt transport process in the soil column under different water addition conditions and investigate the relationship between the soil water and salt transport process and the spectral reflectance of the image on the soil surface. The observation results of the soil column show that the soil water and salt transportation process conforms to the basic transportation law of “salt moves together with water, and when water evaporates, salt is retained in the soil weight”. The salt accumulation phenomenon increases the image spectral reflectance of the surface layer of the soil column, while soil temperature has no effect on the reflectance. As the water percolates down, water and salt accumulate at the bottom of the soil column. The salinity index decreases instantly after the addition of brine and then tends to increase slowly. The experimental results indicate that this work can capture the relationship between the water and salt transport process and remote sensing spectra, which can provide theoretical basis and reference for soil water salinity monitoring.

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Publication Details

Journal
Remote Sensing
Published
2024-09-14
DOI
https://doi.org/10.3390/rs16183421
Citations
1
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
0.21

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article

The Link between Surface Visible Light Spectral Features and Water–Salt Transfer in Saline Soils—Investigation Based on Soil Column Laboratory Experiments

Lijing Han, Chuanmei Zhu, Shaofeng Qin, Jianli Ding et al.
1 citations
Remote Sensing
Soil Geostatistics and Mapping
0.21
article

The Link between Surface Visible Light Spectral Features and Water–Salt Transfer in Saline Soils—Investigation Based on Soil Column Laboratory Experiments

Lijing Han, Chuanmei Zhu, Shaofeng Qin, Jianli Ding, Shuang Zhao, Yong Zhang, Jinjie Wang
article en
1 citations

Abstract

Monitoring soil salinity with remote sensing is difficult, but knowing the link between saline soil surface spectra, soil water, and salt transport processes might help in modeling for soil salinity monitoring. In this study, we used an indoor soil column experiment, an unmanned aerial vehicle multispectral sensor camera, and a soil moisture sensor to study the water and salt transport process in the soil column under different water addition conditions and investigate the relationship between the soil water and salt transport process and the spectral reflectance of the image on the soil surface. The observation results of the soil column show that the soil water and salt transportation process conforms to the basic transportation law of “salt moves together with water, and when water evaporates, salt is retained in the soil weight”. The salt accumulation phenomenon increases the image spectral reflectance of the surface layer of the soil column, while soil temperature has no effect on the reflectance. As the water percolates down, water and salt accumulate at the bottom of the soil column. The salinity index decreases instantly after the addition of brine and then tends to increase slowly. The experimental results indicate that this work can capture the relationship between the water and salt transport process and remote sensing spectra, which can provide theoretical basis and reference for soil water salinity monitoring.

Remote SensingVol. 16(18)
MediaTek (China) (CN), Wuzhou University (CN), Xinjiang Institute of Engineering (CN), Shandong University of Science and Technology (CN), Xinjiang University (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 50%
Soil Geostatistics and Mapping
0.21
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