DataBases (DB) are a widespread source of data, useful for many applications in different scientific fields. The present contribution describes an automatic procedure to access, download and store open access data from different sources, to be processed in a GIS environment. In particular, it refers to the specific need of the authors to manage both meteorological data (pressure and temperature) and GNSS (Global Navigation Satellite System) Zenith Total Delay (ZTD) estimates. Such data allow to produce Precipitable Water Vapor (PWV) maps, thanks to the so called GNSS for Meteorology (G4M) procedure, developed through GRASS GIS software ver. 7.4, for monitoring in time and interpreting severe meteorological events. Actually, the present version of the procedure includes the meteorological pressure and temperature data coming from NOAA’s Integrated Surface Database (ISD), whereas the ZTD data derive from the RENAG DB, that collects ZTD estimates for 181 GNSS Permanent Stations (PSs) from 1998 to 2015 in the French-Italian boundary region. Several Python scripts have been implemented to manage the download of data from NOAA and RENAG DBs, their import on a PostgreSQL/PostGIS geoDB, besides the data elaboration with GRASS GIS to produce PWV maps. The key features of the data management procedure are its scalability and versatility for different sources of data and different contexts. As a future development, a web-interface for the procedure will allow an easier interaction for the users both for post-processing and real-time data. The data management procedure repository is available at https://github.com/gtergeomatica/G4M-data

A procedure to manage open access data for post-processing in GIS environment

Benvenuto, Lorenzo;Marzocchi, Roberto;Ferrando, Ilaria;Federici, Bianca;Sguerso, Domenico
2018-01-01

Abstract

DataBases (DB) are a widespread source of data, useful for many applications in different scientific fields. The present contribution describes an automatic procedure to access, download and store open access data from different sources, to be processed in a GIS environment. In particular, it refers to the specific need of the authors to manage both meteorological data (pressure and temperature) and GNSS (Global Navigation Satellite System) Zenith Total Delay (ZTD) estimates. Such data allow to produce Precipitable Water Vapor (PWV) maps, thanks to the so called GNSS for Meteorology (G4M) procedure, developed through GRASS GIS software ver. 7.4, for monitoring in time and interpreting severe meteorological events. Actually, the present version of the procedure includes the meteorological pressure and temperature data coming from NOAA’s Integrated Surface Database (ISD), whereas the ZTD data derive from the RENAG DB, that collects ZTD estimates for 181 GNSS Permanent Stations (PSs) from 1998 to 2015 in the French-Italian boundary region. Several Python scripts have been implemented to manage the download of data from NOAA and RENAG DBs, their import on a PostgreSQL/PostGIS geoDB, besides the data elaboration with GRASS GIS to produce PWV maps. The key features of the data management procedure are its scalability and versatility for different sources of data and different contexts. As a future development, a web-interface for the procedure will allow an easier interaction for the users both for post-processing and real-time data. The data management procedure repository is available at https://github.com/gtergeomatica/G4M-data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1093737
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