APPLICATION OF POLYNOMIAL TRANSFORMATION IN GEOREFERENCE OF GRAPHIC CADASTRAL PLANS
APPLICATION OF POLYNOMIAL TRANSFORMATION IN GEOREFERENCE OF GRAPHIC CADASTRAL PLANS
DOI:
https://doi.org/10.46687/jsar.v30i1.480Keywords:
Affine transformation, Polynomial transformation, Georeferencing, Cadastral plans, Collinearity, Runge phenomenonAbstract
Polynomial transformation is a classic mathematical tool in geodesy, used to convert coordinates between different reference systems. It is mainly used in cases where the exact geometric or physical model of the relationship between the systems is unknown, as well as in the presence of significant local deformations in the source data. In practice, this method is used in: transformation between coordinate systems (including local), approximation of heights when creating geoid models, localization in GNSS measurements, as well as in specific tasks in photogrammetry and laser scanning. One of its most widespread applications remains the georeferencing of raster images.
This paper investigates the specifics of applying polynomial transformation for georeferencing purposes. The main emphasis is placed on the dependence of the results on the configuration and the number of control points used. An analysis is made and recommendations are formulated for their optimal distribution on the image. The mathematical requirement for uniform grid coverage in a minimum of n+1 columns and rows (where n is the degree of the polynomial) is justified as a condition for avoiding singularity. Additionally, the negative effects of the collinearity of the control points on the computational stability are considered, as well as the approaches for identifying the Runge phenomenon (appearance of high-amplitude oscillations) in the extrapolation zones along the boundaries of the transformed range.
References
Bolstad, P., & Manson, S. (2022). GIS Fundamentals: A First Text on Geographic Information Systems (7th ed.). Eider Press Inc. ISBN: 978-0-9717647-5-0.
Boyanov, G. Cadastre and property register. Sofia: UACEG, 2008. ISBN 978-954-724-034-6.
Dobrev, S. Problems with keepeing cadastral maps up to date for coastal regions. MATTEH 2022: Conference proceedings. Vol. 2. Shumen: Konstantin Preslavsky University Press, p. 211-214, ISSN 1314-3921.
Ghilani, Charles D. Adjustment Computations: Spatial Data Analysis. 6th ed. Hoboken, NJ: John Wiley & Sons, 2017. 720 p. ISBN 978-1-119-38598-1. DOI: 10.1002/9781119385103.
Iliffe, Jonathan & Lott, Roger. Datums and Map Projections: For Remote Sensing, GIS and Surveying. 2nd ed. Dunbeath, Scotland: Whittles Publishing, 2008. 192 p. ISBN 978-1-904445-47-0.
Kheloufi, N., Kahlouche, S., & Lamara, R. A. (2009). Non-linear Least Squares for geodetic adjustment and coordinates transformation. Geophysical Research Abstracts, Vol. 11, EGU2009-333.
Kirilova, K., Yanchev, K. Redefining the capabilities of the unmanned aerial system for the needs of the cadastre. MATTEH 2020: Conference proceedings. Vol. 2. Shumen: Konstantin Preslavsky University Press, p. 255-261, ISSN 1314-3921.
Mikhail, Edward M., Bethel, James S. & McGlone, J. Chris. Introduction to Modern Photogrammetry. New York: John Wiley & Sons, 2001. 479 p. ISBN 978-0-471-30924-6.
Mikrenska-Černeva, K., B. Aleksandrov, P. Pavlov. Geodesy. Sofia: UACEG, 2021. ISBN 978-619-91481-2-0.
Niyazi-Yusuf, M. History of the regulations in the field of cadastre. ANNUAL OF KONSTANTIN PRESLAVSKI UNIVERSITY OF SHUMEN. Faculty of technical sciences, Vol. X E, Shumen: Konstantin Preslavsky University Press, 2020, p. 163-177. ISSN: 1311-834X.
Schaffrin, B. & Felus, Y. A. On total least-squares adjustment with constraints. // A Window on the Future of Geodesy. Vol. 128. Berlin, Heidelberg: Springer, 2005, pp. 417–421. ISBN 978-3-540-24055-6. DOI: 10.1007/3-540-27432-4_71.
Wolf, Paul R., DeWitt, Bon A. & Wilkinson, Benjamin E. Elements of Photogrammetry with Applications in GIS. 4th ed. New York: McGraw-Hill Education, 2014. 696 p. ISBN 978-0-07-176112-3.
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2026 JOURNAL SCIENTIFIC AND APPLIED RESEARCH

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
https://orcid.org/0000-0003-3668-6713