Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/12655
DC FieldValueLanguage
dc.contributor.authorAsimakis, Fylaktos-
dc.contributor.authorYfantidou, Anastasia-
dc.date.accessioned2018-08-10T11:19:46Z-
dc.date.available2018-08-10T11:19:46Z-
dc.date.issued2017-03-
dc.identifier.citation5th International Conference on Remote Sensing and Geoinformation of the Environment, 2017, Paphos, Cyprus, 20-23 Marchen_US
dc.identifier.urihttps://hdl.handle.net/20.500.14279/12655-
dc.descriptionProceedings of SPIE - The International Society for Optical Engineering, 2017, Volume 10444, Article number 104440Len_US
dc.description.abstractNatural hazards like earthquakes can result to enormous property damage, and human casualties in mountainous areas. Italy has always been exposed to numerous earthquakes, mostly concentrated in central and southern regions. Last year, two seismic events near Norcia (central Italy) have occurred, which led to substantial loss of life and extensive damage to properties, infrastructure and cultural heritage. This research utilizes remote sensing products and GIS software, to provide a database of information. We used both SAR images of Sentinel 1A and optical imagery of Landsat 8 to examine the differences of topography with the aid of the multi temporal monitoring technique. This technique suits for the observation of any surface deformation. This database is a cluster of information regarding the consequences of the earthquakes in groups, such as property and infrastructure damage, regional rifts, cultivation loss, landslides and surface deformations amongst others, all mapped on GIS software. Relevant organizations can implement these data in order to calculate the financial impact of these types of earthquakes. In the future, we can enrich this database including more regions and enhance the variety of its applications. For instance, we could predict the future impacts of any type of earthquake in several areas, and design a preliminarily model of emergency for immediate evacuation and quick recovery response. It is important to know how the surface moves, in particular geographical regions like Italy, Cyprus and Greece, where earthquakes are so frequent. We are not able to predict earthquakes, but using data from this research, we may assess the damage that could be caused in the future.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© 2017 SPIE.en_US
dc.subjectEarthquakesen_US
dc.subjectGISen_US
dc.subjectHazard predictionen_US
dc.subjectNatural hazardsen_US
dc.subjectOptical imageryen_US
dc.subjectRemote Sensingen_US
dc.subjectSARen_US
dc.titleUsing remote sensing to predict earthquake impactsen_US
dc.typeConference Papersen_US
dc.doihttps://doi.org/10.1117/12.2279669en_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationHarokopio Universityen_US
dc.subject.categoryCivil Engineeringen_US
dc.countryCyprusen_US
dc.countryGreeceen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
cut.common.academicyear2016-2017en_US
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypeconferenceObject-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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