A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique

In this paper we present a laser profiler, whose main aim is the determination of agricultural soil roughness. Its working principle is based on the acquisition of an image of an object illuminated by a laser beam and on the use of 3D computer vision techniques to obtain the reconstruction of the sc...

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Autores principales: Barber, Matias Ernesto, Pepe, Carolina, Perna, Pablo Alejandro, Grings, Francisco Matías, Thibeault, Marc, Karszenbaum, Haydee
Publicado: 2008
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Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814244_v2_n1_pII731_Barber
http://hdl.handle.net/20.500.12110/paper_97814244_v2_n1_pII731_Barber
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id paper:paper_97814244_v2_n1_pII731_Barber
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spelling paper:paper_97814244_v2_n1_pII731_Barber2023-06-08T16:37:22Z A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique Barber, Matias Ernesto Pepe, Carolina Perna, Pablo Alejandro Grings, Francisco Matías Thibeault, Marc Karszenbaum, Haydee Profilers Rough surfaces Soil roughness 3D computer vision Agricultural soils Autocorrelation functions Correlation lengths Laser profilers Laser scanning Novel methods Profilers Rough surfaces Soil moisture maps Soil roughness Working principles Computer vision Groundwater Regression analysis Remote sensing Soil moisture Surface measurement Three dimensional Two dimensional Lasers In this paper we present a laser profiler, whose main aim is the determination of agricultural soil roughness. Its working principle is based on the acquisition of an image of an object illuminated by a laser beam and on the use of 3D computer vision techniques to obtain the reconstruction of the scanned object. One of the most important purposes of this device is the attainment of the soil RMS height (s) and the correlation length (l) related to the autocorrelation function. These are fundamental inputs to derive soil moisture maps from soil backscattering data. © 2008 IEEE. Fil:Barber, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Pepe, C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Perna, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Grings, F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Thibeault, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Karszenbaum, H. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2008 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814244_v2_n1_pII731_Barber http://hdl.handle.net/20.500.12110/paper_97814244_v2_n1_pII731_Barber
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Profilers
Rough surfaces
Soil roughness
3D computer vision
Agricultural soils
Autocorrelation functions
Correlation lengths
Laser profilers
Laser scanning
Novel methods
Profilers
Rough surfaces
Soil moisture maps
Soil roughness
Working principles
Computer vision
Groundwater
Regression analysis
Remote sensing
Soil moisture
Surface measurement
Three dimensional
Two dimensional
Lasers
spellingShingle Profilers
Rough surfaces
Soil roughness
3D computer vision
Agricultural soils
Autocorrelation functions
Correlation lengths
Laser profilers
Laser scanning
Novel methods
Profilers
Rough surfaces
Soil moisture maps
Soil roughness
Working principles
Computer vision
Groundwater
Regression analysis
Remote sensing
Soil moisture
Surface measurement
Three dimensional
Two dimensional
Lasers
Barber, Matias Ernesto
Pepe, Carolina
Perna, Pablo Alejandro
Grings, Francisco Matías
Thibeault, Marc
Karszenbaum, Haydee
A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique
topic_facet Profilers
Rough surfaces
Soil roughness
3D computer vision
Agricultural soils
Autocorrelation functions
Correlation lengths
Laser profilers
Laser scanning
Novel methods
Profilers
Rough surfaces
Soil moisture maps
Soil roughness
Working principles
Computer vision
Groundwater
Regression analysis
Remote sensing
Soil moisture
Surface measurement
Three dimensional
Two dimensional
Lasers
description In this paper we present a laser profiler, whose main aim is the determination of agricultural soil roughness. Its working principle is based on the acquisition of an image of an object illuminated by a laser beam and on the use of 3D computer vision techniques to obtain the reconstruction of the scanned object. One of the most important purposes of this device is the attainment of the soil RMS height (s) and the correlation length (l) related to the autocorrelation function. These are fundamental inputs to derive soil moisture maps from soil backscattering data. © 2008 IEEE.
author Barber, Matias Ernesto
Pepe, Carolina
Perna, Pablo Alejandro
Grings, Francisco Matías
Thibeault, Marc
Karszenbaum, Haydee
author_facet Barber, Matias Ernesto
Pepe, Carolina
Perna, Pablo Alejandro
Grings, Francisco Matías
Thibeault, Marc
Karszenbaum, Haydee
author_sort Barber, Matias Ernesto
title A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique
title_short A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique
title_full A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique
title_fullStr A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique
title_full_unstemmed A novel method for 2-D agricultural soil roughness characterization based on a laser scanning technique
title_sort novel method for 2-d agricultural soil roughness characterization based on a laser scanning technique
publishDate 2008
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97814244_v2_n1_pII731_Barber
http://hdl.handle.net/20.500.12110/paper_97814244_v2_n1_pII731_Barber
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