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Abstract:

The fitting of a plane to data points is essential to the geosciences. However, it is recognized that the reliability of these best fit planes depends upon the point set distribution and geometry, evaluated in terms of the eigen-based parameters derived from the moment of inertia analysis. Despite its significance, few studies have addressed the uncertainties of the analysis, which can adversely affect the reproduction of results one of the cornerstones of scientific endeavor. Aiming to contribute toward the neglected issue of the moment of inertia precision, we have developed a bootstrap resampling scheme to empirically discover the distribution of uncertainties in the orientation of best fit planes. Dispersion of the bootstrapped normal vectors to the best fit plane is regarded as a measure of precision, evaluated with the maximum angular distance from the optimal solution. This rationale was tested using Monte Carlo-generated samples covering a comprehensive range of shape parameters to assess the dependence between eigen parameters and their inherent bias. Our results show that the oblateness of the point cloud is a robust parameter to assess the reliability of the best fit plane. Given this, the method was then applied to a publicly available lidar data set. We argue that georeferenced point clouds with an oblateness parameter greater than 3 and 1.5 may be placed at 95% confidence levels of 5° and 10°, respectively. We propose using these values as thresholds to obtain robust best fit planes, guaranteeing reproducible results for scientific research. ©2018. American Geophysical Union. All Rights Reserved.

Registro:

Documento: Artículo
Título:A Nonparametric Approach for Assessing Precision in Georeferenced Point Clouds Best Fit Planes: Toward More Reliable Thresholds
Autor:Gallo, L.C.; Cristallini, E.O.; Svarc, M.
Filiación:Instituto de Geociencias Básicas, Aplicadas y Ambientales de Buenos Aires, Departamento de Ciencias Geológicas, Facultad de Ciencias Exactas y Naturales, Ciudad Universitaria, Buenos Aires, Argentina
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
Laboratorio de Modelado Geológico, Instituto de Estudios Andinos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Laboratorio de Termocronología (La.Te Andes), Consejo Nacional de Investigaciones Científicas y Técnicas, Salta, Argentina
Departamento de Matemática y Ciencias, Universidad de San AndrésVIC, Argentina
Palabras clave:best fit plane; bootstrap statistics; moment of inertia analysis; Monte Carlo simulation; orientation of structural heterogeneities; bootstrapping; inertia; Monte Carlo analysis; precision; simulation; threshold
Año:2018
Volumen:123
Número:11
Página de inicio:10,297
Página de fin:10,308
DOI: http://dx.doi.org/10.1029/2018JB016319
Título revista:Journal of Geophysical Research: Solid Earth
Título revista abreviado:J. Geophys. Res. Solid Earth
ISSN:21699313
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_21699313_v123_n11_p10,297_Gallo

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Citas:

---------- APA ----------
Gallo, L.C., Cristallini, E.O. & Svarc, M. (2018) . A Nonparametric Approach for Assessing Precision in Georeferenced Point Clouds Best Fit Planes: Toward More Reliable Thresholds. Journal of Geophysical Research: Solid Earth, 123(11), 10,297-10,308.
http://dx.doi.org/10.1029/2018JB016319
---------- CHICAGO ----------
Gallo, L.C., Cristallini, E.O., Svarc, M. "A Nonparametric Approach for Assessing Precision in Georeferenced Point Clouds Best Fit Planes: Toward More Reliable Thresholds" . Journal of Geophysical Research: Solid Earth 123, no. 11 (2018) : 10,297-10,308.
http://dx.doi.org/10.1029/2018JB016319
---------- MLA ----------
Gallo, L.C., Cristallini, E.O., Svarc, M. "A Nonparametric Approach for Assessing Precision in Georeferenced Point Clouds Best Fit Planes: Toward More Reliable Thresholds" . Journal of Geophysical Research: Solid Earth, vol. 123, no. 11, 2018, pp. 10,297-10,308.
http://dx.doi.org/10.1029/2018JB016319
---------- VANCOUVER ----------
Gallo, L.C., Cristallini, E.O., Svarc, M. A Nonparametric Approach for Assessing Precision in Georeferenced Point Clouds Best Fit Planes: Toward More Reliable Thresholds. J. Geophys. Res. Solid Earth. 2018;123(11):10,297-10,308.
http://dx.doi.org/10.1029/2018JB016319