The aim of my Ph.D. research is to create a methodology for recovery, storage, access and disseminate glaciological data, starting from the development of a spatial data infrastructure (SDI) and use it to study the evolution of the glaciers in relation with climate change. My research is part of the project of interest Nextdata (www.nextdataproject.it). In the first two years a geodatabase for glaciological data was built. A new structure that can contain data about world non polar ice core characterization (IDB1) was implemented. To overlap IDB1 critical issues a new structure was set-up with this improvements: A repositioning methodology was set-up to increase the accuracy of coordinates of the ice cores, different entities with information about project of perforation, drilling-site, references of data and additional information about ice core were added to the structure. During the third year of research the new geodatabase IDB2 was linked with glaciological databases of glaciers containing spatial, geomorphometric and other information. A new part was developed to store data coming from geomorphological analysis. In particular two entities about glaciers were added: the first, Glacier_Code_tab stores the union between the different glaciers databases such as GLIMS, RGI, WGI, WGMS id for each perforated or not perforated glaciers. The second one, Glacier_Data_Tab contains the geomorphological parameters such as Flow line length, min and max elevation, averaged slope and aspect calculate using a GIS algorithm developed. A GIS module called GlacierDataModule (GDM) was developed also during the third year to provide detailed information to calibrate minimal glacier model (MGM) to assess glaciers response to climatic fluctuations and to linkage the geomorphological parameters with climate variability. The procedure requires for each glacier, as inputs DTMs, POLYGONs and FLOW LINEs. The flow lines was calculated starting from the results of r.flow algorithms and after a subjective evaluation based on morphological parameters the most important flow lines were digitalized. The algorithm was applied at 34 glaciers of great alpine region (GAR) that are the glaciers with the longest measurements of mass balance, the primary data needed to run the minimal model. Input data required to GDM were recovered from IDB2 and ASTER GDEMv2 was used as DEM input source. Results of GDM on GAR was used to populate IDB2 in an iterative way and used to calibrate the MGM to assess glaciers response to climatic fluctuations. Geomorphological data coming from the spatial analysis on glaciers was also used to compare the glaciers and find some behaviour useful to evaluate the glacier distribution along the GAR. The results of this analysis shows a clear climatic characteristic of the glaciers of GAR. Only 34 glaciers was evaluated but the results was comparable to the results presents by Evans in his study where 6561 glaciers on GAR were taken in account (Evans, I.S., 2006). A geoportal with a webgis available at: http://geomatic.disat.unimib.it/home/geomatic/idb2/ was developed to share this data. In conclusion during my Ph.D. a SDI contain glaciological data was set-up, drawn and implemented. SDI allowed until now at the scientific community to modelling the suitability for ice core drilling of mountains glaciers and provide a input parameters to run a GIS module developed. GIS Module is used to obtain geomorphological parameters to calibrate minimal model, evaluate the glaciers response at climatic fluctuations through the glacier distribution along the GAR. The IDB2 will be also used in the future to identify paleo-climatic proxy that could be useful, within the interaction of other paleo-climatic proxies (lake sediments; marine sediments; pollen and corals), to reconstruct the last 2K years of climate variability in Italy.

L’obiettivo del progetto di ricerca è creare una metodologia per ricercare, archiviare e diffondere dati glaciologici partendo dallo sviluppo di una infrastruttura di dati spaziali (SDI) che possa essere utile allo studio dell’evoluzione glaciale in relazione ai cambiamenti climatici. Questa ricerca è parte del progetto di interesse nazionale NextData (www.nextdataproject.it). Nei primi due anni è stato sviluppato un geodatabase contenente dati riguardanti la caratterizzazione chimico-fisica di carote di ghiaccio. La prima versione del geodb presentava delle criticità che sono state superate con l’implementazione della seconda versione dove sono stati applicati i seguenti miglioramenti: Sviluppata e applicata una metodologia di riposizionamento, aggiunta di differenti entità con informazioni riguardanti il progetto di perforazione, il sito di perforazione, le references dei dati e tutte le informazioni aggiuntive utili per la classificazione e la caratterizzazione delle ice cores. Durante il terzo anno di ricerca alla nuova struttura creata e chiamata IDB2 sono stati uniti diversi database glaciologici contenenti dati spaziali, geomorfometrici e informazioni su ghiacciai. E’ stata sviluppata una nuova parte dell’infrastruttura capace di accogliere dati derivanti da analisi geomorfologiche, nello specifico sono state aggiunte due entità chiamate rispettivamente Glacier_code_tab e Glacier_data_tab. La prima archivia l’unione tra differenti banche dati glaciologiche. Nello specifico gli ID del GLIMS, RGI, WGI, WGMS sono stati aggiunti e collegati ad ogni ghiacciaio perforato. La seconda contiene dati geomorfologici calcolati tramite un algoritmo GIS sviluppato durante il terzo anno. L’algoritmo sviluppato in ambiente GIS è stato chiamato GLACIER DATA MODULE (GDM). L’algoritmo è stato sviluppato per poter ricavare informazioni dettagliate per la calibrazione dei Minimal glacier model (MGM), una famiglia di modelli glaciologici per la predizione dell’andamento dei ghiacciai in risposta alle fluttuazioni climatiche. La procedura richiede per ogni ghiacciaio come input DTM, poligoni riportanti il confine glaciale e le linee di flusso del ghiaccio. Queste ultime sono state calcolate partendo dal risultato dell’algoritmo r.flow e dopo un attenta analisi geomorfologica è stata individuata la flow line principale del ghiacciaio analizzato. L’algoritmo è stato applicato a 34 ghiacciai della catena alpina con le più lunghe misurazione di bilanci di massa, parametro fondamentale per la calibrazione dei MGM. I dati di input per l’algoritmo sono stati ricavati dalla SDI IDB2 e come DTM è stato usato ASTER GDEMv2. I risultati del GDM sono stati usati per popolare IDB2 chiudendo così l’iteratività della SDI creata e sono stati usati per calibrare i MGM utili a valutare la risposta dei ghiacciai ai cambiamenti climatici. I dati geomorfologici ricavati dall’analisi spaziale sui ghiacciai sono anche stati usati per definire degli andamenti utili a definire la distribuzione dei ghiacci alpini lungo la catena montuosa. Per concludere la creazione della SDI, un geoportale è stato sviluppato ed è disponibile al sito: http://geomatic.disat.unimib.it/home/geomatic/idb2/. Concludendo, durante il mio dottorato ho sviluppato una SDI contenente dati glaciologici. La struttura ha permesso fino ad oggi di modellare la suscettibilità di ghiacciai non polari alla perforazione e di calibrare modelli glaciologici semplici come i MGM utilizzati per valutare la risposta dei ghiacciai ai cambiamenti climatici. La struttura verrà usata in futuro come base per lo sviluppo di banca dati riguardate tutti i proxy paleoclimatici utili alla ricostruzione del clima nella penisola italiana degli ultimi 2k anni.

(2016). Development of a Glaciological Spatial Data Infrastructure to assess glacier response to climatic fluctuation.. (Tesi di dottorato, Università degli Studi di Milano-Bicocca, 2016).

Development of a Glaciological Spatial Data Infrastructure to assess glacier response to climatic fluctuation.

MATTAVELLI, MATTEO
2016

Abstract

The aim of my Ph.D. research is to create a methodology for recovery, storage, access and disseminate glaciological data, starting from the development of a spatial data infrastructure (SDI) and use it to study the evolution of the glaciers in relation with climate change. My research is part of the project of interest Nextdata (www.nextdataproject.it). In the first two years a geodatabase for glaciological data was built. A new structure that can contain data about world non polar ice core characterization (IDB1) was implemented. To overlap IDB1 critical issues a new structure was set-up with this improvements: A repositioning methodology was set-up to increase the accuracy of coordinates of the ice cores, different entities with information about project of perforation, drilling-site, references of data and additional information about ice core were added to the structure. During the third year of research the new geodatabase IDB2 was linked with glaciological databases of glaciers containing spatial, geomorphometric and other information. A new part was developed to store data coming from geomorphological analysis. In particular two entities about glaciers were added: the first, Glacier_Code_tab stores the union between the different glaciers databases such as GLIMS, RGI, WGI, WGMS id for each perforated or not perforated glaciers. The second one, Glacier_Data_Tab contains the geomorphological parameters such as Flow line length, min and max elevation, averaged slope and aspect calculate using a GIS algorithm developed. A GIS module called GlacierDataModule (GDM) was developed also during the third year to provide detailed information to calibrate minimal glacier model (MGM) to assess glaciers response to climatic fluctuations and to linkage the geomorphological parameters with climate variability. The procedure requires for each glacier, as inputs DTMs, POLYGONs and FLOW LINEs. The flow lines was calculated starting from the results of r.flow algorithms and after a subjective evaluation based on morphological parameters the most important flow lines were digitalized. The algorithm was applied at 34 glaciers of great alpine region (GAR) that are the glaciers with the longest measurements of mass balance, the primary data needed to run the minimal model. Input data required to GDM were recovered from IDB2 and ASTER GDEMv2 was used as DEM input source. Results of GDM on GAR was used to populate IDB2 in an iterative way and used to calibrate the MGM to assess glaciers response to climatic fluctuations. Geomorphological data coming from the spatial analysis on glaciers was also used to compare the glaciers and find some behaviour useful to evaluate the glacier distribution along the GAR. The results of this analysis shows a clear climatic characteristic of the glaciers of GAR. Only 34 glaciers was evaluated but the results was comparable to the results presents by Evans in his study where 6561 glaciers on GAR were taken in account (Evans, I.S., 2006). A geoportal with a webgis available at: http://geomatic.disat.unimib.it/home/geomatic/idb2/ was developed to share this data. In conclusion during my Ph.D. a SDI contain glaciological data was set-up, drawn and implemented. SDI allowed until now at the scientific community to modelling the suitability for ice core drilling of mountains glaciers and provide a input parameters to run a GIS module developed. GIS Module is used to obtain geomorphological parameters to calibrate minimal model, evaluate the glaciers response at climatic fluctuations through the glacier distribution along the GAR. The IDB2 will be also used in the future to identify paleo-climatic proxy that could be useful, within the interaction of other paleo-climatic proxies (lake sediments; marine sediments; pollen and corals), to reconstruct the last 2K years of climate variability in Italy.
DE AMICIS, MATTIA GIOVANNI MARIA
ZUCCA, FRANCESCO
Climate Change, SDI, Glacier, non polar Ice core, GIS
Cambiamenti climatici, SDI, ghiacciai, carote di ghiaccio non polare, SIT
GEO/04 - GEOGRAFIA FISICA E GEOMORFOLOGIA
English
24-feb-2016
SCIENZE AMBIENTALI - 09R
28
2014/2015
open
(2016). Development of a Glaciological Spatial Data Infrastructure to assess glacier response to climatic fluctuation.. (Tesi di dottorato, Università degli Studi di Milano-Bicocca, 2016).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/102679
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