<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study compares two interpolation methods in the problem of a local GNSS/levelling (quasi) geoid modelling. It uses raw data, no global geopotential model is involved. The methods differ as to the complexity of modelling procedure and theoretical background, they are ordinary kriging/least-squares collocation with constant trend and inverse distance weighting (IDW). The comparison itself was done through leave-one-out and random (Monte Carlo) cross-validation. Ordinary kriging and IDW performance was tested with a local (using limited number of data) and global (using all available data) neighbourhoods using various planar covariance function models in case of kriging and various exponents (power parameter) in case of IDW. For the study area both methods assure an overall accuracy level, measured by mean absolute error, root mean square error and median absolute error, of less than 1 cm. Although the method of IDW is much simpler, a suitably selected parameters (also trend removal) may contribute to differences between methods that are virtually negligible (fraction of a millimetre).</p>
</abstract>

This study compares two interpolation methods in the problem of a local GNSS/levelling (quasi) geoid modelling. It uses raw data, no global geopotential model is involved. The methods differ as to the complexity of modelling procedure and theoretical background, they are ordinary kriging/least-squares collocation with constant trend and inverse distance weighting (IDW). The comparison itself was done through leave-one-out and random (Monte Carlo) cross-validation. Ordinary kriging and IDW performance was tested with a local (using limited number of data) and global (using all available data) neighbourhoods using various planar covariance function models in case of kriging and various exponents (power parameter) in case of IDW. For the study area both methods assure an overall accuracy level, measured by mean absolute error, root mean square error and median absolute error, of less than 1 cm. Although the method of IDW is much simpler, a suitably selected parameters (also trend removal) may contribute to differences between methods that are virtually negligible (fraction of a millimetre).

A crossvalidation-based comparison of kriging and IDW in local GNSS/levelling quasigeoid modelling

Department of Integrated Geodesy and Cartography, Faculty of Geo-Data Science, Geodesy and Environmental Engineering

Reports on Geodesy and Geoinformatics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This study compares two interpolation methods in the problem of a local GNSS/levelling (quasi) geoid modelling. It uses raw data, no global geopotential model...

A crossvalidation-based comparison of kriging and IDW in local GNSS/levelling quasigeoid modelling

Pubblicato online: 28 ott 2022

Pagine: 1 - 7

Ricevuto: 06 ago 2022

Accettato: 21 set 2022

DOI: https://doi.org/10.2478/rgg-2022-0004

Parole chiave
quasigeoid, kriging, least squares collocation, IDW, conversion surface, cross-validation

© 2022 Marcin Ligas et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A crossvalidation-based comparison of kriging and IDW in local GNSS/levelling quasigeoid modelling

Pubblicato online: 28 ott 2022

Pagine: 1 - 7

Ricevuto: 06 ago 2022

Accettato: 21 set 2022

DOI: https://doi.org/10.2478/rgg-2022-0004

Parole chiavequasigeoid, kriging, least squares collocation, IDW, conversion surface, cross-validation

© 2022 Marcin Ligas et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
quasigeoid, kriging, least squares collocation, IDW, conversion surface, cross-validation