RRCM densification at low cost and without centering errors

Main Article Content

Rovane Marcos de França
https://orcid.org/0000-0003-4867-6053
Ivandro Klein
https://orcid.org/0000-0003-4296-592X
Luis Augusto Koenig Veiga
https://orcid.org/0000-0003-4026-5372

Abstract

In locations where GNSS (Global Navigation Satellite System) positioning is not adequate, such as urban canyons, the densification of reference networks is carried out by measuring angles and distances with a total station. In this sense, some of the largest error sources are the station point and the reflector prism on the target point centering errors. Recently, França, Klein and Veiga (2023) proposed the multiple free station (MFS) method, which eliminates centering errors and significantly reduces the number of measurements, providing better accuracy and higher productivity than conventional methods such as triangulateration and traverses. In this work, we apply the MFS for the first time to a real problem of network densification and show that the MFS meets all the technical criteria of the technical standard NBR14166/2022, which deals with the Municipal Cadastral Reference Network (RRCM). We analyzed the aforementioned method for the 3D case with the inclusion of the vertical component, unlike França, Klein and Veiga (2023) where only the horizontal positioning was considered. In addition, we have developed and validated a new low-cost 360° reflector target, which significantly reduces the cost of conventional 360° reflector prisms. We also show that the MFS can be applied with real observations in any least squares adjustment software, without the implementation and propagation of covariances of virtual or indirect observations. The standard deviations presented a mean and maximum value of 4.1 mm and 4.7 mm (horizontal) and 5.7 mm and 7.6 mm (vertical). Thus, considering the accuracy, productivity, and low-cost aspects demonstrated here, we propose the application of the MFS in the densification of RRCM in municipalities that still do not have RRCM compatible with NBR14166/2022.

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How to Cite
FRANÇA , R. M. de .; KLEIN, I.; VEIGA, L. A. K. RRCM densification at low cost and without centering errors. Brazilian Journal of Cartography, [S. l.], v. 76, 2024. DOI: 10.14393/rbcv76n0a-69641. Disponível em: https://seer.ufu.br/index.php/revistabrasileiracartografia/article/view/69641. Acesso em: 30 dec. 2024.
Section
Territorial Cadastre

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