Diffuse reflectance spectroscopy for assessing various soil properties: a review

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Abstract

Hyperspectral imaging has proven to be a powerful tool in environmental applications. This review article focuses on implementation of noncommercial hyperspectral data in soil property predictions suitable for engineering geological applications. Prior attention has been given to spectroscopic processing and further data analysis in case studies of mineral composition, grain size, soil moisture and soil organic carbon. We considered PRISMA, EnMAP and DESIS perceptively to be the most suitable sensors for soil mapping according to the specifics of Russian environmental research, described modern pre-processing techniques and use-cases for hyperspectral imagery in soil studies. Pros and contras of spectroscopic approaches are discussed from engineering geological point of view. We concluded that the main problem preventing the local further development of spectroscopy is lack of soil samples for Russian territory available in published spectroscopic libraries. Several points were raised regarding orthorectification and atmospheric corrections, i.e., the need for data of high resolution and requirement of processing improvement might be still a problem for soil applications. On the other side, large amount of data available for scientific use, high accuracy and spatial resolution of hyperspectral imagery stimulates us to find a solution of mentioned problems. This work tends to demonstrate advantages of spectroscopic approaches to direct spectral data interpretation and it is aimed at drawing more attention of researchers in engineering geology to spectroscopic approaches.

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About the authors

D. S. Savchenko

Lomonosov Moscow State University; Sergeev Institute of Environmental Geoscience, Russian Academy of Sciences

Author for correspondence.
Email: danilsavch@yandex.ru

Geological Faculty

Russian Federation, Leninskiye Gory 1, Moscow, 119991; Ulansky per. 13, bld. 2, Moscow, 101000

E. A. Voznesensky

Lomonosov Moscow State University; Sergeev Institute of Environmental Geoscience, Russian Academy of Sciences

Email: eugene@geoenv.ru

Geological Faculty

Russian Federation, Leninskiye Gory 1, Moscow, 119991; Ulansky per. 13, bld. 2, Moscow, 101000

R. R. Timigaleeva

Lomonosov Moscow State University

Email: timirgaleevarr@my.msu.ru

Institute of Complex Systems Mathematical Research

Russian Federation, Leninskiye Gory 1, Moscow, 119991

A. V. Korotaev

Lomonosov Moscow State University; HSE University; Institute for African Studies, Russian Academy of Sciences

Email: akorotаyev@gmail.com

Faculty of Global Studies, Centre for Stability and Risk Analysis

Russian Federation, Leninskiye Gory 1, Moscow, 119991; Myasnitskaya ul. 20, Moscow, 101000; ul. Spiridonovka 30/1, Moscow, 123001

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2. Fig. 1. Spectral reflectivity of clay soils of alluvial genesis in northeastern Brazil. The solid line shows the reflectivity spectrum of a natural sample, the dotted line shows the spectrum with the addition of gypsum [54].

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3. Fig. 2. Spectral reflectivity of clay soils with different organic matter content for samples from Poznan, Poland [26].

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4. Fig. 3. Spectral reflectance of clay soils collected from the New Mexico shrub steppe with an OM content of less than 1%. The volumetric moisture content is given on the right for each graph [47].

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