Prediction of Soil Moisture Content and Soil Salt Concentration from Hyperspectral Laboratory and Field Data

Xu, Chaoqian; Zeng, Wenzhi; Huang, Jiesheng; Wu, Jingwei; Leeuwen, Willem J. D. van

doi:10.3390/rs8010042

Cited by 48 publications

(24 citation statements)

References 48 publications

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“…This means that when the moisture content increases, the spectral reflectance decreases. Researches also showed that the soil reflectance decreases with soil salt content [35,36]. In the current study, we took dried soil samples as the study object, which can be considered to have the same moisture content, and the main factors that determine the spectral reflectance are salt content and surface roughness.…”

Section: Discussionmentioning

confidence: 95%

Correlation between Spectral Characteristics and Physicochemical Parameters of Soda-Saline Soils in Different States

Ren

Zhao

et al. 2019

Remote Sensing

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The spectral features of soils are a comprehensive representation of their physicochemical parameters, surface states, and internal structures. To date, spectral measurements have been mostly performed for powdered soils and smooth aggregate soils, but rarely for cracked soils; a common state of soda-saline soils. In this study, we measured the spectral features of 57 saline soil samples in powdered, aggregate, and cracked states for comparison. We then explored in depth the factors governing soil spectral features to build up simple and multiple linear regression models between the spectral features and physicochemical parameters (salt content, Na+, pH, and electronic conductivity (EC)) of saline soils in different states. We randomly selected 40 samples to construct the models, and used the remaining 17 samples for validation. Our results indicated that the regression models worked more effectively in predicting physicochemical parameters for cracked soils than for other soils. Subsequently, the crack ratio (CR) was introduced into the regression models to modify the spectra of soils in powdered and aggregate states. The accuracy of prediction was improved, evidenced by a 2–11% decrease in the parameters mean absolute error (MAE).

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Section: Discussionmentioning

confidence: 95%

Correlation between Spectral Characteristics and Physicochemical Parameters of Soda-Saline Soils in Different States

Ren

Zhao

et al. 2019

Remote Sensing

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“…When salt efflorescence is partial, especially at coarse resolution, different soil type (e.g., texture, color) and roughness, presence of sparse vegetation, and surface water content can have confounding effects on salinity estimations. However, these effects can be accounted for, as presented by Xu et al (2016).…”

Section: Surface Soil Salinitymentioning

confidence: 99%

Moving Forward on Remote Sensing of Soil Salinity at Regional Scale

Scudiero

Corwin

Anderson

et al. 2016

Front. Environ. Sci.

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Soil salinity undermines global agriculture by reducing crop yield and impairing soil quality. Irrigation management can help control salinity levels within the soil root-zone. To best manage water and soil resources, accurate regional-scale inventories of soil salinity are needed. The past decade has seen several successful applications of soil salinity remote sensing. Two salinity remote sensing approaches exist: direct assessment based on analysis of surface soil reflectance (the most popular approach) and indirect assessment of root-zone (e.g., 0-1 m) soil salinity based on analysis of crop canopy reflectance. In this perspective paper, we call on researchers and funding agencies to pay greater attention to the indirect approach because it is better suited for surveying agriculturally important lands. A joint effort between agricultural producers, irrigation specialists, environmental scientists, and policy makers is needed to better manage saline agricultural soils, especially because of projected future water scarcity in arid and semi-arid irrigated areas. The remote sensing community should focus on providing the best tools for mapping and monitoring salinity in such areas, which are of vital relevance to global food production.

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“…In the aforementioned studies, the laboratory measurements were collected using carefully prepared or dilute soil specimens under controlled conditions. Fewer studies were conducted under field conditions [23,25,26]. Among the numerous developed soil reflectance correlations in the literature, other soil parameters of interest have included clay content [9,14,24,[27][28][29][30], grain size [9,28,29,31], soil plasticity [24,32,33] and matric potential [24].…”

Section: Introductionmentioning

confidence: 99%

Development of a Multimode Field Deployable Lidar Instrument for Topographic Measurements of Unsaturated Soil Properties: Instrument Description

2019

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The hydrological and mechanical behavior of soil is determined by the moisture content, soil water (matric) potential, fines content, and plasticity. However, these parameters are often difficult or impractical to determine in the field. Remote characterization of soil parameters is a non-destructive data collection process well suited to large or otherwise inaccessible areas. A ground-based, field-deployable remote sensor, called the soil observation laser absorption spectrometer (SOLAS), was developed to collect measurements from the surface of bare soils and to assess the in-situ condition and essential parameters of the soil. The SOLAS instrument transmits coherent light at two wavelengths using two, continuous-wave, near-infrared diode lasers and the instrument receives backscattered light through a co-axial 203-mm diameter telescope aperture. The received light is split into a hyperspectral sensing channel and a laser absorption spectrometry (LAS) channel via a multi-channel optical receiver. The hyperspectral channel detects light in the visible to shortwave infrared wavelengths, while the LAS channel filters and directs near-infrared light into a pair of photodetectors. Atmospheric water vapor is inferred using the differential absorption of the on- and off-line laser wavelengths (823.20 nm and 847.00 nm, respectively). Range measurement is determined using a frequency-modulated, self-chirped, coherent, homodyne detection scheme. The development of the instrument (transmitter, receiver, data acquisition components) is described herein. The potential for rapid characterization of physical and hydro-mechanical soil properties, including volumetric water content, matric potential, fines content, and plasticity, using the SOLAS remote sensor is discussed. The envisioned applications for the instrument include assessing soils on unstable slopes, such as wildfire burn sites, or stacked mine tailings. Through the combination of spectroradiometry, differential absorption, and range altimetry methodologies, the SOLAS instrument is a novel approach to ground-based remote sensing of the natural environment.

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Prediction of Soil Moisture Content and Soil Salt Concentration from Hyperspectral Laboratory and Field Data

Cited by 48 publications

References 48 publications

Correlation between Spectral Characteristics and Physicochemical Parameters of Soda-Saline Soils in Different States

Correlation between Spectral Characteristics and Physicochemical Parameters of Soda-Saline Soils in Different States

Moving Forward on Remote Sensing of Soil Salinity at Regional Scale

Development of a Multimode Field Deployable Lidar Instrument for Topographic Measurements of Unsaturated Soil Properties: Instrument Description

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