Merging InSAR and GNSS Meteorology: How Can We Mine InSAR and GNSS Databases to Extract and Visualize Information on Atmosphere Processes?

Tipo

Inproceedings

Fecha

2017-11-28

Autores

Giovanni Nico, Amaia Gil Lerchundi, Marco Francesco Quartulli, Pedro Mateus, Joao Catalao

Libro

Proceedings of the 2017 conference on Big Data from Space

@Inproceedings{
author ={Giovanni Nico, Amaia Gil Lerchundi, Marco Francesco Quartulli, Pedro Mateus, Joao Catalao},
title ={Merging InSAR and GNSS Meteorology: How Can We Mine InSAR and GNSS Databases to Extract and Visualize Information on Atmosphere Processes?},
booktitle ={Proceedings of the 2017 conference on Big Data from Space},
publisher ={Publications Office of the European Union,},
editor ={P. Soille and P. G. Marchetti},
address ={Toulouse, France},
date ={2017-11-28},
year ={2017},
pages ={375-378},
keys ={

Meteorology, Sentinel-1, visualization, databases, Numerical Weather Model (NWM), Synthetic Aperture Radar (SAR), SAR Interferometry, Global Navigation Satellite System (GNSS)

},
abstract ={

The use of Numerical Weather Models (NWMs) provides forecasts of meteorological events based on hypothesis on surface cover, boundary layer and other mechanisms of atmosphere processes. In many cases, the selection of appropriate parameters and the tuning of models at the basis of NWMs is made by non-advanced users in a hoc manner. The availability of huge databases of InSAR and GNSS measurements of PWV provides those users a unique possibility to falsify the hypothesis at the basis of their choice of parameters. In this work we introduce features, based on statistical analysis and graph theory, that can help to compare InSAR and GNSS measurements to NWM simulations. From the point of view of the user, the meaning
of comparison is to quickly catch the informative potential of InSAR and GNSS data if assimilated in a NWM.

},
ISSN ={1831-9424},
ISBN ={978-92-79-73527-1},
}