DocumentCode
1963948
Title
GIS-based System for Landslide Early Warning Index Measurement
Author
Bovenga, F. ; Miali, Elena ; Nutricato, Raffaele ; Chiaradia, M.T.
Author_Institution
Politecnico di Bari, Bari
fYear
2007
fDate
25-27 June 2007
Firstpage
78
Lastpage
83
Abstract
Landslides are one of the most serious natural and man induced hazards. The paper presents an innovative system dedicated to the measurement of landslide warning index. The system is based on a geographic information system (GIS) inference engine which properly combine satellite Earth observation (EO) measurements and static geophysical parameters. The system has been developed in the framework of an FP5 European project and it is aimed to provide an operative and flexible tool for public and private entities involved in land management, and in particular in mitigation of both landslide hazard and risk. Particular attention will be devoted to the role that the GIS environment plays as optimal measurement environment since it provides flexible interface between human (both high level geophysical experts and low level end users) and data (heterogeneous data in input to the geophysical model, warning maps in output).
Keywords
alarm systems; geographic information systems; hazards; inference mechanisms; remote sensing; FP5 European project; GIS inference engine; geographic information system; landslide early warning index measurement; landslide hazard-risk; satellite Earth observation measurements; static geophysical parameters; Earth; Engines; Geographic Information Systems; Geophysical measurements; Hazards; Particle measurements; Project management; Risk management; Satellites; Terrain factors; Early Warning; Earth Observation; GIS; Landslide;
fLanguage
English
Publisher
ieee
Conference_Titel
Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2007. VECIMS 2007. IEEE Symposium on
Conference_Location
Ostuni
Print_ISBN
978-1-4244-0820-7
Electronic_ISBN
978-1-4244-0820-7
Type
conf
DOI
10.1109/VECIMS.2007.4373932
Filename
4373932
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