Interpreting deformation results of geodetic network points using the strain models based on different estimation methods

Year 2020, , 49 - 59, 01.02.2020

Haluk Konak , Pakize Küreç Nehbit , Aslıhan Karaöz , Fazilet Cerit

https://doi.org/10.26833/ijeg.581584

Cited By: 3

Abstract

Geodetic Networks designed as Deformation Networks or Continuous Networks are observed in different epochs/ sessions and evaluated as a function of time. Those can be design as global GNSS networks for aim monitoring active tectonic movements or as regional densification geodetic and deformation networks for monitoring local earthquakes and surface movements. The areas covered geodetic networks are assumed as any surface on ellipsoid or sphere. Characteristics of surfaces are analyzed with Geometric Strain Models using deformation data on surface points. In this case, effect rates on geodetic network area are determined from local surface movements or regional active earthquakes and interpreted as experimental. On the other hand, undetermined outliers by model hypothesis test affect coordinate unknowns separately. Outliers cause deformations in certain magnitude on networks points. Therefore, network points strain in different rates and directions. Query of maximum affects caused by these strain rates is a referenced reliability method called "Robustness Analysis in Geodetic Networks”. Mentioned strain rates are modelled by various estimation methods. Thus, deformation results could be interpreted together by the obtained strain components and deformation vector. In this paper, possible strain components belonging to network points are determined with methods of L1 Norm, Least Median Squares (LMS) and Least Squares Estimation (LSE). These estimation methods are tested on KOUSAGA (Kocaeli University Permanent GPS Network). Strain components are estimated by use polyhedrons covered by network points. Obtained results are compared and analyzed according to weakness and strengths of proposed estimation methods.

Keywords

Deformation, Strain, Estimation Methods, KOUSAGA

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