Partitions of normalised multiple regression equations for datum transformations
Multiple regression equations (MREs) provide an empirical direct method of transforming coordinates between geodetic datums. Since they offer a means of modelling distortions, they are capable of a more accurate fit to datum-shift datasets than more basic direct methods. MRE models of datum shifts t...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | Brasil |
| Institución: | Universidade Federal do Paraná (UFPR) |
| Repositorio: | Boletim de Ciências Geodésicas |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/86199 |
| Acceso en línea: | https://revistas.ufpr.br/bcg/article/view/86199 |
| Access Level: | acceso abierto |
| Palabra clave: | multiple regression equations surface polynomials datum transformations geodetic datums |
| Sumario: | Multiple regression equations (MREs) provide an empirical direct method of transforming coordinates between geodetic datums. Since they offer a means of modelling distortions, they are capable of a more accurate fit to datum-shift datasets than more basic direct methods. MRE models of datum shifts traditionally consist of polynomials based on relative latitude and longitude. However, the limited availability of low-power terms often leads to high-power terms being included, and these are a potential cause of instability. This paper introduces three variations based on simple partitions and 2 or 4 smoothly conjoined polynomials. The new types are North/South, East/West and Four-Quadrant. They increase the availability of low-order terms, enabling distortions to be modelled with fewer side effects. Case studies in Great Britain, Slovenia and Western Australia provide examples of partitioned MREs that are more accurate than conventional MREs with the same number of terms. |
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