The manifestation of VIS-NIRS spectroscopy data to predict and map soil texture in the Triffa plain (Morocco)

被引:8
|
作者
Lazaar, Ayoub [1 ]
Pradhan, Biswajeet [2 ]
Naiji, Zakariae [1 ]
Gour, Abdelali [3 ]
El Hammouti, Kamal [1 ]
Andich, Karim [4 ]
Monir, Abdelilah [5 ,6 ]
机构
[1] Mohammed First Univ, Dept Geol, Fac Sci, Oujda, Morocco
[2] Ctr Adv Modelling & Geospatial Informat Syst, Fac Engn & Informat Technol, Sydney, NSW, Australia
[3] Cadi Ayyad Univ, Fac Sci & Tech, Dept Geol, BP 549, Marrakech, Morocco
[4] Natl Inst Agron Res, Dept Geomat & Soil Sci, Oujda, Morocco
[5] Moulay Ismail Univ, Dept Math, EDP, Meknes, Morocco
[6] Moulay Ismail Univ, Sci Comp Team, Fac Sci, Meknes, Morocco
关键词
Partial least squares regression; reflectance spectra; spectroscopy; soil texture; texture mapping; NEAR-INFRARED SPECTROSCOPY; REFLECTANCE SPECTROSCOPY; ORGANIC-MATTER; WATER; GROUNDWATER; REGRESSION; SPECTRA; MODEL; CLAY; PLSR;
D O I
10.48129/kjs.v48i1.8012
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The use of standard laboratory methods to estimate the soil texture is complicated, expensive, and time-consuming and needs considerable effort. The reflectance spectroscopy represents an alternative method for predicting a large range of soil physical properties and provides an inexpensive, rapid, and reproducible analytical method. This study aimed to assess the feasibility of Visible (VIS: 350-700 nm) and Near-Infrared and Short-Wave-Infrared (NIRS: 701-2500 nm) spectroscopy for predicting and mapping the clay, silt, and sand fractions of the soils of Triffa plain (north-east of Morocco). A total of 100 soil samples were collected from the non-root zone of soil (0-20 cm) and then analyzed for texture using the VIS-NIRS spectroscopy and the traditional laboratory method. The partial least squares regression (PLSR) technique was used to assess the ability of spectral data to predict soil texture. The results of prediction models showed excellent performance for the VIS-NIRS spectroscopy to predict the sand fraction with a coefficient of determination R-2 = 0.93 and Root Mean Squares Error (RMSE) =3.72, good prediction for the silt fraction (R-2=0.87; RMSE = 4.55), and acceptable prediction for the clay fraction (R-2 = 0.53; RMSE = 3.72). Moreover, the range situated between 2150 and 2450 nm is the most significant for predicting the sand and silt fractions, while the spectral range between 2200 and 2440 nm is the optimal to predict the clay fraction. However, the maps of predicted and measured soil texture showed an excellent spatial similarity for the sand fraction, a certain difference in the variability of clay fraction, while the maps of silt fraction show a lower difference.
引用
收藏
页码:127 / 137
页数:11
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