Approximate continuation of harmonic functions in geodesy: A spline based least squares approach with regularization

This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.

Feature

Request download

Citation

Citation Options

Identification

*Title:*	Main Title: Approximate continuation of harmonic functions in geodesy: A spline based least squares approach with regularization
*Description:*	Abstract: This paper is concerned with the approximate reconstruction of the earth’s potential field from geometric and gravimetric data. This is an ill-posed problem involving typically large amounts of data which are to be continued by a harmonic function. The standard approach in geodesy is based on spherical harmonics which are globally supported. Thus, a least squares approach for the data fitting yields a linear system of equations with a fully populated system matrix. This becomes computationally prohibitive for large amounts of data and, therefore, presents the biggest bottleneck for fast and efficient computations. Motivated by the early work [24], we propose in this paper an alternative and pose the harmonicity requirement on the continuation together with the data fitting as a minimization problem for a least squares functional with regularization involving the Laplacian. This approach enables the use of locally supported functions in the reconstruction for which we employ tensor products of cubic splines. The linear system resulting from the weighted least squares approach is therefore sparsely populated which allows for iterative solvers of complexity proportional to the total number of unknowns. We extensively study the choice of the regularization parameter balancing the data fit and the harmonicity requirement for both synthetic as well as earth potential data. We compare the results with discretizations using finite differences and finite elements for solving Laplace’s equation.
*Identifier:*	10.1016/j.cam.2012.07.007 (DOI)

Responsible Party

*Creators:*	Gabriela Jager (Author), Angela Kunoth (Author), Wolf-Dieter Schuh (Author)
*Publisher:*	Elsevier
*Publication Year:*	2014

Topic

*TR32 Topic:*	Other
*Related Subprojects:*	C1, C7
*Subjects:*	Keywords: Regularization, Least Squares GEMET Thesaurus entry: mathematical analysis

File Details

*Filename:*	Jager_2013_JCAM.pdf
*Data Type:*	Text - Article
*File Size:*	3.1 MB
*Dates:*	Submitted: 18.03.2011 Available: 20.07.2012
*Mime Type:*	application/pdf
*Data Format:*	PDF
*Language:*	English
*Status:*	Completed

Constraints

*Download Permission:*	Only Project Members
*Download Information:*	Copyright © 2012 Elsevier B.V. All rights reserved.
*General Access and Use Conditions:*	For internal use in TR32 only.
*Access Limitations:*	For internal use in TR32 only.
*Licence:*	[TR32DB] Data policy agreement

Geographic

Specific Information - Publication

*Publication Status:*	Peer-Reviewed
*Review Status:*	Peer reviewed
*Publication Type:*	Article
*Article Type:*	Journal
*Source:*	Journal of Computational and Applied Mathematics
*Source Website:*	http://www.sciencedirect.com/science/article/pii/S037704271200297X#
*Issue:*	1
*Volume:*	237
*Number of Pages:*	21 (62 - 82)

Metadata Details

*Metadata Creator:*	Angela Kunoth
*Metadata Created:*	16.07.2014
*Metadata Last Updated:*	16.07.2014
*Subproject:*	C1
*Funding Phase:*	2
*Metadata Language:*	English
*Metadata Version:*	V50

Metadata Export

Metadata Schema:

Dataset Statistics

*Page Visits:*	768
*Metadata Downloads:*	0
*Dataset Downloads:*	1

Dataset Activity

Feature

Download

top ∧