Mathematical techniques to remove moisture effects from visible-near-infrared-shortwave-infrared soil spectra-review

被引:26
作者
Knadel, Maria [1 ]
Castaldi, F. [2 ]
Barbetti, R. [3 ]
Ben-Dor, E. [4 ]
Gholizadeh, A. [5 ]
Lorenzetti, R. [2 ]
机构
[1] Aarhus Univ, Dept Agroecol, Blichers 20,PO 50, DK-8930 Tjele, Denmark
[2] Natonal Res Council Italy, Inst BioEcon CNR IBE, Rome, Italy
[3] Council Agr Res & Econ, Forestry & Wood CREA FL, Casale Monferrato, Italy
[4] Tel Aviv Univ, Porter Sch Environm & Earth Sci, Dept Geog, Tel Aviv, Israel
[5] Czech Univ Life Sci, Dept Soil Sci & Soil Protect, Prague, Czech Republic
基金
欧盟地平线“2020”;
关键词
Soil moisture; diffuse reflectance spectroscopy; field-moist conditions; algorithms; indices; EXTERNAL PARAMETER ORTHOGONALIZATION; IN-SITU CHARACTERIZATION; REFLECTANCE SPECTROSCOPY; ORGANIC-CARBON; CLAY CONTENT; INORGANIC CARBON; NIR SPECTROSCOPY; PARTICLE-SIZE; PREDICTION; MODEL;
D O I
10.1080/05704928.2022.2128365
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
Visible-near-infrared-shortwave-infrared (VNIR-SWIR) spectroscopy is one of the most promising sensing techniques to meet ever-growing demands for soil information and data. To ensure the successful application of this technique in the field, efficient methods for tackling detrimental moisture effects on soil spectra are critical. In this paper, mathematical techniques for reducing or removing the effects of soil moisture content (SMC) from spectra are reviewed. The reviewed techniques encompass the most common spectral pre-processing and algorithms, as well as less frequently reported methods including approaches within the remote sensing domain. Examples of studies describing their effectiveness in the search for calibration model improvement are provided. Moreover, the advantages and disadvantages of the different techniques are summarized. Future research including further studies on a wider range of soil types, in-field conditions, and systematic experiments considering several SMC levels to enable the definition of threshold values for the effectiveness of the discussed methods is recommended.
引用
收藏
页码:629 / 662
页数:34
相关论文
共 102 条
[1]   Predicting clay content on field-moist intact tropical soils using a dried, ground VisNIR library with external parameter orthogonalization [J].
Ackerson, Jason P. ;
Dematte, Jose A. M. ;
Morgan, Cristine L. S. .
GEODERMA, 2015, 259 :196-204
[2]  
AFNOR, NFX07001 AFNOR, V2006, P07
[3]  
[Anonymous], 2007, APPL NUMERICAL HARMO
[4]   MARMIT: A multilayer radiative transfer model of soil reflectance to estimate surface soil moisture content in the solar domain (400-2500 nm) [J].
Bablet, A. ;
Vu, P. V. H. ;
Jacquemoud, S. ;
Viallefont-Robinet, F. ;
Fabre, S. ;
Briottet, X. ;
Sadeghi, M. ;
Whiting, M. L. ;
Baret, F. ;
Tian, J. .
REMOTE SENSING OF ENVIRONMENT, 2018, 217 :1-17
[5]  
Ben-Dor E., 1999, Remote sensing for the earth sciences: manual of remote sensing. Volume 3., P111
[6]   Quantitative remote sensing of soil properties [J].
Ben-Dor, E .
ADVANCES IN AGRONOMY, VOL 75, 2002, 75 :173-243
[7]   Comparison of Field and Laboratory Wet Soil Spectra in the Vis-NIR Range for Soil Organic Carbon Prediction in the Absence of Laboratory Dry Measurements [J].
Biney, James Kobina Mensah ;
Boruvka, Lubos ;
Chapman Agyeman, Prince ;
Nemecek, Karel ;
Klement, Ales .
REMOTE SENSING, 2020, 12 (18)
[8]   Application of Continuous Wavelet Transform in Examining Soil Spatial Variation: A Review [J].
Biswas, Asim ;
Si, Bing Cheng .
MATHEMATICAL GEOSCIENCES, 2011, 43 (03) :379-396
[9]   Global soil characterization with VNIR diffuse reflectance spectroscopy [J].
Brown, David J. ;
Shepherd, Keith D. ;
Walsh, Markus G. ;
Mays, M. Dewayne ;
Reinsch, Thomas G. .
GEODERMA, 2006, 132 (3-4) :273-290
[10]   Reducing moisture effects on soil organic carbon content prediction in visible and near-infrared spectra with an external parameter othogonalization algorithm [J].
Cao, Yue ;
Bao, Nisha ;
Liu, Shanjun ;
Zhao, Wei ;
Li, Shimeng .
CANADIAN JOURNAL OF SOIL SCIENCE, 2020, 100 (03) :253-262