The thesis research involved a literature review, some data analysis and a study of the nature of tower and pole structures. There has been a vast amount of material published on the topic of deformation surveying, the thesis attempted to compile, organise and condense it to highlight the key points by proposing a methodology for deformation monitoring.



The proposed methodology explains the concepts and ideas of deformation monitoring to give a better understanding of the different methods used to monitor towers.


The main elements of this methodology are:


  • Selection of a Deformation model
  • Measurement instruments & procedures
  • Network design
  • Definition of a Geodetic datum
  • Analysis of results
  • Presentation of results


Some key ideas associated with a deformation study are:


  • Tests of Zero measurement
  • Cancellation of systematic errors
  • Independent and direct measurements
  • Instrument calibration
  • Datum effects

Structural properties of towers

The structural engineering theory and external forces acting on towers were investigated as part of the thesis research. The external forces studied as part of the thesis included solar radiation, wind loads and building movement. The possible deformations were identified by using beam deflection calculations using Young’s modulus of elasticity, thermal expansion and other engineering theory. This study helped make recommendations on mount designs and material types while mounting a GNSS antenna on towers or pole structures.


Survey network adjustments

Deformation analysis on survey networks can be performed by a number of different adjustment methods. Conventional least squares (LS), the L1 robust method and the Free network (Freenets) adjustments were used to perform deformation calculations on test data.

Harvey (2009) provided the examples that have been used in this thesis for testing the different adjustment methods on survey networks.This analysis gave a better understanding of the advantages and limitations of the different methods depending on the application of the survey.


L1 method


The L1 method is considered a robust method as it can cope with errors in input data and adjust a network despite rank defects. The L1 adjustment usually gives a residual larger than the true error and can be used to flag outliers or analyse erroneous input data file which cause conventional least squares to crash or not converge (Harvey, 1993).


While the L1 method is known to highlight observational errors, it has not been widely applied to deformation monitoring.  The research forming this thesis investigated the use of L1 method to find whether displacements were clearer than when LS was applied.


Freenets method


The free network adjustment is a special solution technique where none of the parameters are held fixed during the adjustment of the survey network. This eliminates any datum distortions from possible erroneous starting coordinates in an over constrained solution or datum biases on point error ellipses. This makes it especially useful for high precision engineering surveys and deformation analysis.


The ‘braced quadrilateral’ (Harvey, 2009) in Figure 1 graphically illustrate the effect of a conventional LS adjustment with 1 known coordinate and azimuth held fixed, and a Freenet adjustment. It can be seen that the Freenet solution produces smaller error ellipses due to the unconstrained nature of the adjustment that gives a best ‘overall fit’ solution.


Figure 1 - Conventional least squares (left) and the Freenet (right) adjustment method (Harvey, 2009)