Data/hora: 06/06/2024 14:03:46

Provedor de dados: 	42	
País: 	Brazil	
Título: 	Hybrid Geoid Model: Theory and Application in Brazil	
Autores: 	ARANA,DANIEL; CAMARGO,PAULO O.; GUIMARÃES,GABRIEL N.	
Data: 	2017-09-01	
Ano: 	2017	
Palavras-chave: 	EGM08; GEOIDSP2014; GNSS leveling; MAPGEO2015; Neural network.	
Resumo: 	Determination of the ellipsoidal height by Global Navigation Satellite Systems (GNSS) is becoming better known and used for purposes of leveling with the aid of geoid models. However, the disadvantage of this method is the quality of the geoid models, which degrade heights and limit the application of the method. In order to provide better quality in transforming height using GNSS leveling, this research aims to develop a hybridization methodology of gravimetric geoid models EGM08, MAPGEO2015 and GEOIDSP2014 for the State of São Paulo, providing more consistent models with GNSS technology. Radial Basis Function (RBF) neural networks were used to obtain the corrector surface, based on differences between geoid model undulations and the undulations obtained by GNSS tracking in benchmarks. The experiments showed that the most suitable interpolation for correction modeling is the linear RBF. Checkpoints indicate that the geoid hybrid models feature root mean square deviation   ± 0.107,   ± 0.104 and   ± 0.098 m, respectively. The results shows an improvement of 30 to 40% in consistencies compared with the gravimetric geoids, providing users with better quality in transformation of geometric to orthometric heights.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000401943	
Editor: 	Academia Brasileira de Ciências	
Relação: 	10.1590/0001-3765201720160802	
Formato: 	text/html	
Fonte: 	Anais da Academia Brasileira de Ciências  v.89 n.3 2017	
Fonte: 	info:eu-repo/semantics/openAccess