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Quantitative Soil Spectroscopy Applied and Environmental Soil Science Quantitative Soil Spectroscopy Guest Editors: Sabine Chabrillat, Eyal Ben-Dor, Raphael A. Viscarra Rossel, and Jose ' A. M. Dematte^ Quantitative Soil Spectroscopy Applied and Environmental Soil Science Quantitative Soil Spectroscopy Guest Editors: Sabine Chabrillat, Eyal Ben-Dor, Raphael A. Viscarra Rossel, and JoseA.M.Dematt´ eˆ Copyright © 2013 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “Applied and Environmental Soil Science.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Editorial Board Lynette K. Abbott, Australia William Horwath, USA Nikolla Qafoku, USA Joselito M. Arocena, Canada Davey Jones, UK Peter Shouse, USA Nanthi Bolan, Australia Matthias Kaestner, Germany B. Singh, Australia Robert L. Bradley, Canada Heike Knicker, Spain Keith Smettem, Australia Artemi Cerda, Spain Takashi Kosaki, Japan Marco Trevisan, Italy Claudio Cocozza, Italy Yongchao Liang, China Antonio Violante, Italy Hong J. Di, New Zealand Teodoro M. Miano, Italy Paul Voroney, Canada Oliver Dilly, Germany Amaresh K. Nayak, India Jianming Xu, China Michael A. Fullen, UK Yong Sik Ok, Republic of Korea Ryusuke Hatano, Japan Alessandro Piccolo, Italy Contents Quantitative Soil Spectroscopy, Sabine Chabrillat, Eyal Ben-Dor, Raphael A. Viscarra Rossel, and JoseA.M.Dematt´ eˆ Volume 2013, Article ID 616578, 3 pages Effects of Subsetting by Carbon Content, Soil Order, and Spectral Classification on Prediction of Soil Total Carbon with Diffuse Reflectance Spectroscopy, Meryl L. McDowell, Gregory L. Bruland, Jonathan L. Deenik, and Sabine Grunwald Volume 2012, Article ID 294121, 14 pages Investigations into Soil Composition and Texture Using Infrared Spectroscopy (2-14 µm), Robert D. Hewson, Thomas J. Cudahy, Malcolm Jones, and Matilda Thomas Volume 2012, Article ID 535646, 12 pages The Effects of Spectral Pretreatments on Chemometric Analyses of Soil Profiles Using Laboratory Imaging Spectroscopy, Henning Buddenbaum and Markus Steffens Volume 2012, Article ID 274903, 12 pages Spatially Explicit Estimation of Clay and Organic Carbon Content in Agricultural Soils Using Multi-Annual Imaging Spectroscopy Data, Heike Gerighausen, Gunter Menz, and Hermann Kaufmann Volume 2012, Article ID 868090, 23 pages A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem, Anita Bayer, Martin Bachmann, Andreas Muller,¨ and Hermann Kaufmann Volume 2012, Article ID 971252, 20 pages Using Reflectance Spectroscopy and Artificial Neural Network to Assess Water Infiltration Rate into the Soil Profile, Naftali Goldshleger, Alexandra Chudnovsky, and Eyal Ben-Dor Volume 2012, Article ID 439567, 9 pages Spectral Estimation of Soil Properties in Siberian Tundra Soils and Relations with Plant Species Composition, Harm Bartholomeus, Gabriela Schaepman-Strub, Daan Blok, Roman Sofronov, and Sergey Udaltsov Volume 2012, Article ID 241535, 13 pages Quantitative Analysis of Total Petroleum Hydrocarbons in Soils: Comparison between Reflectance Spectroscopy and Solvent Extraction by 3 Certified Laboratories, Guy Schwartz, Eyal Ben-Dor, and Gil Eshel Volume 2012, Article ID 751956, 11 pages Hindawi Publishing Corporation Applied and Environmental Soil Science Volume 2013, Article ID 616578, 3 pages http://dx.doi.org/10.1155/2013/616578 Editorial Quantitative Soil Spectroscopy Sabine Chabrillat,1 Eyal Ben-Dor,2 Raphael A. Viscarra Rossel,3 and José A. M. Demattê4 1 Section of Remote Sensing, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany 2 The Remote Sensing Laboratory, Department of Geography and Human Environment, Tel-Aviv University, P.O. Box 39040, Ramat Aviv, 69978 Tel-Aviv, Israel 3 Soil and Landscape Program, CSIRO Land and Water, Bruce E. Butler Laboratory, Clunies-Ross Street Black Mountain, P.O. Box 1666, Canberra, ACT 2601, Australia 4 Soil Science Department, Luiz de Queiroz College of Agriculture, SaoPaulo,UniversityofPiracicaba,SP13418-900,Brazil˜ Correspondence should be addressed to Sabine Chabrillat; [email protected] Received 13 January 2013; Accepted 13 January 2013 Copyright © 2013 Sabine Chabrillat et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Interest in the use of visible-near infrared reflectance spec- relateprimarilytothefollowingattributes.(i)Soilwater, troscopy for the determination of mineralogical composition a key variable in hydrologic cycle, controls processes such in soils and planetary surfaces has been demonstrated since as infiltration and discharge with consequences for plant the 1970s with the development of databases of minerals growth, soil erosion, and land degradation. (ii) Soil carbon spectra recorded in the laboratory by Hunt and Salisbury. (content and composition), through its key role in the carbon A little later, in the early 1980s, the first spectral database cycle, is an important variable in global climate models. Soil (or library) of American soils was generated by Stoner and organic matter, of which carbon is a major part, holds a Baumgardner. In the mid-1980s, several workers demon- large proportion of nutrients, cations, and trace elements strated that different soil attributes could be estimated from that are needed for plant growth. (iii) Soil mineralogy and the spectral reflectance measurement and the quantitative texture are important soil properties as they affect physical, era of soil spectroscopy begun. The attractiveness of soil chemical, and biological soil processes. Other soil parameters mightalsobeestimatedthrougheitherdirectorindirect spectroscopy is that measurements are rapid and estimates relationships of soil reflectance with the chemical, physical, of soil properties are inexpensive compared to conventional and biological characteristics of the soil matrix. soil analyses. Nowadays, research on quantitative soil spec- In this regard, optical and infrared sensing covering troscopy for the prediction of soil properties, prompted by the visible, infrared, and thermal parts of the electromag- developments in multivariate statistics and chemometrics, is netic spectrum, respectively, have shown good potential for continuing to grow. Over the past decades, the availability of retrieving information on soil attributes. Across this spectral new high signal-to-noise ratio hyperspectral sensors that can range, three regions sensitive to soil properties can be defined be mounted on airborne platforms or that can be used in the as follows: laboratory and the field opened significant new possibilities toward the quantitative analyses of the physical and bio- (i) The visible-near infrared (VNIR) spectral region from chemical composition of the Earth’s soil. 0.4 to 1 m contains information on soil color, iron The spectral reflectance of soil is a cumulative property content and composition, soil water, and organic that derives from the inherent spectral behaviour of het- matter. erogeneous combinations of minerals, organic matter, and (ii) The near infrared (NIR) which also referred asthe water molecules in the soil. Studies on soil spectroscopy short-wave infrared (SWIR) in remote sensing from 2 Applied and Environmental Soil Science 1to2.5m contains information on phyllosilicates, theuppersurfaceisusedtogetherwithon-ground(or most sorosilicates, hydroxides, some sulphates, am- proximal) soil spectroscopy for global soil characterization phiboles, carbonates, soil water, and organic matter. and monitoring. A number of bench top and portable spectrometers In this context, the main focus of this special issue is to combine the VNIR and the SWIR to provide spectra present current research on soil applications of reflectance in the vis–NIR range from 0.4 to 2.5 m. spectroscopy at both point and imagery domains, illustrating (iii) The mid-infrared (mid-IR), which is also referred state-of-the-art methods in quantitative soil spectroscopy. to as the thermal infrared (TIR) in remote sensing, Our principal objective is that this issue demonstrates the ranges from 2.5 to 25 mincludingthemedium potentialofsoilspectroscopyforthequantitativedescription (MWIR) and long-wave (LWIR) infrared spectral of spatial distribution of soils and their properties. The special regions (3–5 and 8–14 m) that are atmospheric win- issue received 13 papers from all over the world covering dows. This spectral region contains information on diverse topics. Of those, after a peer review process, 8 were quartz, feldspars, silicate minerals, mafic, clay, car- considered for publication. bonate mineral group, and organic compounds. M. L. McDowell et al. discuss the effects of subsetting by carbon content, soil order, and spectral classification for While the chemical attributes influencing soil reflectance are the prediction of soil total carbon using the VNIR, SWIR, basedonabsorptionofradiationbychemicalcompounds and TIR (0.4–14 m) spectral regions associated with partial in selected frequencies, a soil spectrum is also affected by least squares regression (PLSR) models based on diffuse physical characteristics of the soil such as particle size, reflectance information received by a point spectrometer.
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