Data/hora: 11/06/2024 07:23:41

Provedor de dados: 	5	
País: 	France	
Título: 	Integrating Prior Knowledge and Locally Varying Parameters with Moving-GeoStatistics: Methodology and Application to Bathymetric Mapping	
Autores: 	Magneron, Cedric; Jeannee, Nicolas; Le Moine, Olivier; Bourillet, Jean-francois.	
Data: 	2010	
Ano: 	2010	
Resumo: 	The paper aims at presenting an innovative methodology, called M-GS (M-GeoStatistics), which is fully dedicated to the local optimization of parameters involved in variogram-based models. M-GS considers the structural and computational parameters as a set of dependant parameters to be spatially optimized. The optimization process, which may be guided by objective or subjective criteria, is carried out during a M-structural analysis phase that leads to a set of spatially variable structural and computational parameters. The methodology is applied for bathymetry mapping. The availability of accurate seafloor estimates is essential for numerous oceanographic projects, including hydrographic, oceanographic and biological models, sedimentary processes, etc. Seafloor usually presents strong non stationarity and complex structures, such as small channels with varying orientations, spatially varying measurements errors, local heterogeneities for coastal areas, or deep canyons within general gentle slope for continental margins. The adequacy of the M-GS methodology in this framework is illustrated and compared with classical estimates for the Marenne-Oleron coast (West of France). Moreover such methodology could be used to input different local structures into a general model in the aim of a regional synthesis.	
Tipo: 	Text	
Idioma: 	Inglês	
Identificador: 	http://archimer.ifremer.fr/doc/00071/18200/15768.pdf	
Editor: 	7th International Conference on Geostatistics for Environmental Applications, Southampton, ENGLAND, SEP, 2008	
Relação: 	http://archimer.ifremer.fr/doc/00071/18200/	
Formato: 	application/pdf	
Fonte: 	2010 Springer