Information depth of NIR/SWIR soil reflectance spectroscopy

Proximal and remote sensing techniques in the optical domain are cost-effective alternatives to standard soil property characterization methods. However, the extent of light penetration into the soil sample, also termed soil information depth, is not well understood. In this study a new analytical m...

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Bibliographic Details
Published in:Remote sensing of environment Vol. 256; p. 112315
Main Authors: Norouzi, Sarem, Sadeghi, Morteza, Liaghat, Abdolmajid, Tuller, Markus, Jones, Scott B., Ebrahimian, Hamed
Format: Journal Article
Language:English
Published: New York Elsevier Inc 01.04.2021
Elsevier BV
Subjects:
Clay soils
cost effectiveness
environment
Information depth
Light penetration
Light reflection
Mathematical models
Near infrared radiation
Optical properties
Optical remote sensing
Organic matter
Particle size
Particle size distribution
Reflectance
reflectance spectroscopy
Remote sensing
Remote sensing techniques
Sandy soils
Sensing techniques
Short wave radiation
Size distribution
Soil properties
Soil reflectance spectrum
Spectroscopy
Spectrum analysis
texture
Wavelengths
Particle size distribution
Information depth
Soil reflectance spectrum
Optical remote sensing
ISSN:0034-4257, 1879-0704
Online Access:Get full text
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Summary:Proximal and remote sensing techniques in the optical domain are cost-effective alternatives to standard soil property characterization methods. However, the extent of light penetration into the soil sample, also termed soil information depth, is not well understood. In this study a new analytical model that links the particle size distribution and soil reflectance in the near infrared (NIR) and shortwave infrared (SWIR) bands of the electromagnetic spectrum is introduced. The model enables the partitioning of measured reflectance spectra into surface and volume (subsurface) contributions, thereby yielding insights about the soil information depth. The model simulations indicate that the surface reflectance contribution to the total reflectance is significantly higher than the volume reflectance contribution for a broad range of soils that vastly differ in texture, mineralogical composition and organic matter contents. The ratio of volume to total reflectance is higher for sandy soils than for clayey soils, especially at longer optical wavelengths, but the ratio rarely exceeds 15%. Therefore, the light reflection from dry soils is predominantly a surface phenomenon and the information depth in most soils rarely exceeds 1 mm. The results of this study reveal an intimate physical relationship between soil reflectance and the particle size distribution in the NIR/SWIR range, which opens a potential new avenue for retrieval of the particle size distribution from remotely sensed reflectance via a universal process-based approach. •A new model links the particle size distribution and soil NIR/SWIR reflectance.•It partitions reflectance spectra into surface and volume contributions.•It shows that light reflectance from dry soils is dominantly a surface phenomenon.•The volume/total reflectance ratio is higher for coarse than for fine soils.•The model opens new avenues for remote sensing of soil hydraulic properties.
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ISSN:0034-4257
1879-0704
DOI:10.1016/j.rse.2021.112315