Authors:
R. Erenoglu Yildiz Technical University Department of Geomatics Engineering 34210 Davutpaşa, Istanbul Turkey

Search for other papers by R. Erenoglu in
Current site
Google Scholar
PubMed
Close
and
S. Hekimoglu Yildiz Technical University Department of Geomatics Engineering 34210 Davutpaşa, Istanbul Turkey

Search for other papers by S. Hekimoglu in
Current site
Google Scholar
PubMed
Close
Restricted access

Geodetic measurements are commonly used for monitoring volcanic activities and crustal motions. Together with paleoseismic and other geologic observations, geodetic data are central in long-term forecast of earthquake hazards. Presence of outliers in geodetic data strongly affects least squares principle, which are extensively used for data analysis and modeling in geodesy. Thus, the positions of the geodetic points are computed as biased. Robust methods are techniques used to construct estimates describing well data majority. In this study, some robust methods and conventional tests for outliers have been tested on a number of linear and nonlinear geodetic adjustment models. The results are presented to illustrate the effectiveness of the methods. Furthermore, we discuss how the effectiveness of the methods changes depending on various key parameters for geodetic networks, i.e. the number of outliers, the magnitude of outliers, the degree of freedom, the number of observation and number of unknowns.

  • Collapse
  • Expand

To see the editorial board, please visit the website of Springer Nature.

Manuscript Submission: HERE

For subscription options, please visit the website of Springer Nature.

Acta Geodaetica et Geophysica
Language English
Size B5
Year of
Foundation
2013
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó Springer
Nature Switzerland AG
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2213-5812 (Print)
ISSN 2213-5820 (Online)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Jun 2024 18 0 44
Jul 2024 38 0 0
Aug 2024 10 0 0
Sep 2024 16 0 0
Oct 2024 42 0 0
Nov 2024 19 0 0
Dec 2024 0 0 0