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    Comparative Review of Molodensky-Badekas and Burša-Wolf Methods for Coordinate Transformation

    81684.pdf (1.077Mb)
    Access Status
    Open access
    Authors
    Abbey, Donald
    Featherstone, Will
    Date
    2020
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Abbey, D.A. and Featherstone, W.E. 2020. Comparative Review of Molodensky-Badekas and Burša-Wolf Methods for Coordinate Transformation. Journal of Surveying Engineering. 146 (3): Article No. 04020010.
    Source Title
    Journal of Surveying Engineering
    DOI
    10.1061/(ASCE)SU.1943-5428.0000319
    ISSN
    0733-9453
    Faculty
    Faculty of Science and Engineering
    School
    School of Earth and Planetary Sciences (EPS)
    Remarks

    This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29SU.1943-5428.0000319

    URI
    http://hdl.handle.net/20.500.11937/81642
    Collection
    • Curtin Research Publications
    Abstract

    © 2020 American Society of Civil Engineers. J. Badekas reinterpreted M. S. Molodensky's three-dimensional similarity transformation as a vector solution using a centroid. The solution has since been (mis)interpreted by some others with inconsistent reference to the methods of both Molodensky and Badekas, principally relating to the translation vector and the stochastic model. This appears to have led to incorrect claims that the Molodensky-Badekas method is superior to the Helmert similarity and Burša-Wolf methods. This paper reviews the development and description of the original Badekas method, reconfirming its equivalence to the Burša-Wolf method in the forward direction, and provides an alternative solution that suits the same-formula reversal common in commercial surveying software. It is also demonstrated that the Molodensky-Badekas method has no inherent superiority over the Burša-Wolf method, has an ambiguous functional model, and nominally underestimates its parameter statistics when these are compared directly with those from the Burša-Wolf method.

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