HIERARCHICAL DATA FUSION WITH PHOTOGRAMMETRIC APPLICATIONS

When two datasets are fused using least-squares adjustment, usually all the results will be affected by some change, even the reference data that are meant to provide information of such high quality that they should remain stable. In order to avoid this effect, the sequential adjustment is to be re...

ver descrição completa

Detalhes bibliográficos
Autores: Schaffrin, Burkhard, Cothren, Jackson
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:Brasil
Recursos:Universidade Federal de Uberlândia (UFU)
Repositorio:Revista brasileira de cartografia - RBC (Online)
Idioma:inglés
OAI Identifier:oai:ojs.www.seer.ufu.br:article/43492
Acesso em linha:https://seer.ufu.br/index.php/revistabrasileiracartografia/article/view/43492
Access Level:acceso abierto
Palavra-chave:Hierarchical
least-squares
photogrammetri
Descrição
Resumo:When two datasets are fused using least-squares adjustment, usually all the results will be affected by some change, even the reference data that are meant to provide information of such high quality that they should remain stable. In order to avoid this effect, the sequential adjustment is to be replaced by a strictly hierarchical method in which the esti-mation procedure is designed to reproduce everything that belongs to a "higher category" and to perform an adjustment in the least-squares sense for everything else. After presenting such a suboptimal estimator, but with the "reproducing property," this technique is applied to the integration of photogrammetric networks of substantially different scales.