scholarly journals Features of Remote Determination of Humus Content in Arable Soils

2019 ◽  
Author(s):  
Anatoly F. Gurov ◽  
Vera A. Shirokova ◽  
Alla O. Khutorova ◽  
Yulia D. Yurova
Keyword(s):  
Humus Content ◽  
Arable Soils ◽  
Remote Determination

Instrument for the remote determination of viscosity and density in hostile environments

1992 ◽  
Vol 63 (9) ◽  
pp. 4192-4195 ◽  
Author(s):  
K. K. Li ◽  
A. Schneider ◽  
R. L. Abraham
Keyword(s):  
Remote Determination ◽  
Hostile Environments

scholarly journals Soil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 418 ◽  
Author(s):  
Alexander Erler ◽  
Daniel Riebe ◽  
Toralf Beitz ◽  
Hans-Gerd Löhmannsröben ◽  
Robin Gebbers
Keyword(s):  
Precision Agriculture ◽  
Multivariate Regression ◽  
Humus Content ◽  
Laser Induced Breakdown Spectroscopy ◽  
Soil Parameters ◽  
Soil Matrix ◽  
Regression Methods ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.

Development of a broadband lidar system for remote determination of aerosol size distributions

2002 ◽  
Vol 13 (3) ◽  
pp. 383-390 ◽  
Author(s):  
James B Gillespie ◽  
David A Ligon ◽  
Paul M Pellegrino ◽  
Nicholas F Fell ◽  
Nicholas J Wood
Keyword(s):  
Size Distributions ◽  
Lidar System ◽  
Remote Determination
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