Visible and Near-Infrared Spectroscopy as a Tool for Soil Classification and Soil Profile Description

Guillaume Debaene, Piotr Bartmiński, Jacek Niedźwiecki, Tomasz Miturski

Abstract


This paper presents preliminary results of the use of visible and near-infrared (VIS -NIR) spectroscopy for soil classification and soil profile examination. Three experiments involving (1) three different soil types (Albic Luvisol, Gleyic Phaeozem, Brunic Arenosol), (2) three artificial micro-plots with similar texture (loamy sand, Gleyic Phaeozem) but different soil organic carbon (SOC) content and (3) a soil profile (Fluvisol) have been investigated using VIS -NIR spectroscopy. Results indicated that VIS -NIR is a promising technique for preliminary soil description and can classify soils according to soil properties (especially SOC ) and horizons. Instead of complex chemical and physical analyses involved in routine soil profile classification, VIS-NIR spectroscopy is suggested as a useful, rapid, and inexpensive tool for soil profile investigation.


Keywords


VIS -NIR spectroscopy, soil remote sensing, spectral properties

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References


Aïchi, H., Fouad, Y., Walter, C., ViscarraRossel, R.A., Lili Chabaane, Z., Sanaa, M., 2009. Regional Predictions of Soil Organic Carbon Content from Spectral Reflectance Measurements. Biosystems Engineering, 104, 3: 442–446.

Barthès, B.G., Brunet, D., Hien, E., Enjalric, F., Conche, S., Freschet, G.T., d’Annunzio, R., Toucet-Louri, J., 2008. Determining the Distributions of Soil Carbon and Nitrogen in Particle Size Fractions Using Near-Infrared Reflectance Spectrum of Bulk Soil Samples. Soil Biology and Biochemistry, 40, 6: 1533–1537.

Bartmiński, P., Plak, A., Dębicki, R., 2012. Buffer Capacity of Soil as Indicator of Urban Forest Soil Resistance to Degradation. Polish Journal of Soil Science, 45, 2: 129–136.

Ben-Dor, E., Heller, D., Chudnovsky, A., 2008. A Novel Method of Classifying Soil Profiles in the Field Using Optical Means. Soil Science Society of America Journal, 72, 4: 1113–1123.

Cierniewski, J., Kaźmierowski, C., Krolewicz, S., 2015. Evaluation of the Effects of Surface Roughness on the Relationship Between Soil BRF Data and Broadband Albedo. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 4: 1528–1533.

Croft, H., Anderson, K., Kuhn, N.J., 2009. Characterizing Soil Surface Roughness Using a Combined Structural and Spectral Approach. European Journal of Soil Science, 60, 3: 431–442.

Debaene, G., Niedźwiecki, J., Pecio, A., 2013. On-the-Go Mapping of Soil Organic Carbon Content in Western Poland. Proceedings of the 3rd Global Workshop on Proximal Soil Sensing: 248–251.

Debaene, G., Niedźwiecki, J., Pecio, A., 2010. Visible and Near-Infrared Spectrophotometer for Soil Analysis: Preliminary Results. Polish Journal of Agronomy, 3: 3–9.

Debaene, G., Niedźwiecki, J., Pecio, A., Żurek, A., 2014a. Effect of the Number of Calibration Samples on the Prediction of Several Soil Properties at the Farm-Scale. Geoderma, 214–215: 114–125.

Debaene, G., Pikula, D., Niedzwiecki, J., 2014b. Use of VIS-NIRS for Land Management Classification with a Support Vector Machine and Prediction of Soil Organic Carbon and Other Soil Properties. Ciencia e Investigación AGRARIA , 41, 1: 21–32.

Demattê, J.A., Campos, R.C., Alves, M.C., Fiorio, P.R., Nanni, M.R., 2004. Visible–NIR Reflectance: A New Approach on Soil Evaluation. Geoderma, 121, 1–2: 95–112.

Eshel, G., Levy, G.J., Singer, M.J., 2004. Spectral Reflectance Properties of Crusted Soils under Solar Illumination. Soil Science Society of America Journal, 68, 6: 1982–1991.

Fabre, S., Briottet, X., Lesaignoux, A., 2015. Estimation of Soil Moisture Content from the Spectral Reflectance of Bare Soils in the 0.4–2.5 μm Domain. Sensors, 15, 2: 3262–3281.

Kweon, G., Maxton, C., 2013. Soil Organic Matter Sensing with an On-the-Go Optical Sensor. Biosystems Engineering, 115, 1: 66–81.

Madari, B.E., Reeves, J.B., Machado, P.L., Guimarães, C.M., Torres, E., McCarty, G.W., 2006. Mid- and Near-Infrared Spectroscopic Assessment of Soil Compositional Parameters and Structural Indices in Two Ferralsols. Geoderma, 136, 1–2: 245–259.

Paz-Kagan, T., Shachak, M., Zaady, E., Karnieli, A., 2014. A Spectral Soil Quality Index (SSQI) for Characterizing Soil Function in Areas of Changed Land Use. Geoderma, 230–231: 171–184.

Roberts, C.A., Workman, Jr. J., Reeves, III J.B., Workman, J., Shenk, J., 2004.Understanding and Using the Near-Infrared Spectrum as an Analytical Method, In: Roberts, C.A., Workman, J., Reeves, J.B. (eds.), Near-Infrared Spectroscopy in Agriculture. Agronomy Monograph. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America: 2–10.

Stenberg, B., Viscarra Rossel, R.A., Mouazen, A.M., Wetterlind, J., 2010.Visible and Near Infrared Spectroscopy in Soil Science, In: Sparks, D.L. (ed.), Advances in Agronomy: 163–215, http://dx.doi.org/10.1016/S0065-2113(10)07005-7

Vasques, G.M., Demattê, J., Viscarra Rossel, R. A., Ramírez-López, L., Terra, F.S., 2014. Soil Classification Using Visible/Near-Infrared Diffuse Reflectance Spectra from Multiple Depths. Geoderma, 223–225: 73–78.

Waiser, T.H., Morgan C.L. S., Brown, D.J., Hallmark, C.T., 2007. In Situ Characterization of Soil Clay Content with Visible Near-Infrared Diffuse Reflectance Spectroscopy. Soil Science Society of America Journal, 71, 2: 389–396.

Wenjun, J., Zhou, S., Jingyi, H., Shuo, L., Motta, A., 2014. In Situ Measurement of Some Soil Properties in Paddy Soil Using Visible and Near-Infrared Spectroscopy. PLoS ONE , 9, 8: e105708, http://dx.doi.org/10.1371/journal.pone.0105708

World reference base for soil resources, 2014. International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports. FAO, Rome.




DOI: http://dx.doi.org/10.17951/pjss.2017.50.1.1
Date of publication: 2017-08-30 11:16:04
Date of submission: 2017-03-15 14:38:02


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