Please use this identifier to cite or link to this item:
http://hdl.handle.net/2122/7435
DC Field | Value | Language |
---|---|---|
dc.contributor.authorall | Pulvirenti, L.; Sapienza University of Rome | en |
dc.contributor.authorall | Chini, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia | en |
dc.contributor.authorall | Pierdicca, N.; Sapienza University of Rome | en |
dc.contributor.authorall | Guerriero, L.; Tor Vergata University | en |
dc.contributor.authorall | Ferrazzoli, P.; Tor Vergata University | en |
dc.date.accessioned | 2012-01-20T07:31:44Z | en |
dc.date.available | 2012-01-20T07:31:44Z | en |
dc.date.issued | 2011-01-08 | en |
dc.identifier.uri | http://hdl.handle.net/2122/7435 | en |
dc.description.abstract | The COSMO-SkyMed mission offers a unique opportunity to obtain radar data characterized by short revisit time, thus being useful for flood evolution mapping. A procedure to monitor an inundation event using multitemporal COSMO-SkyMed data is presented in this paper. The methodology is based on an automatic image segmentation technique and on the use of a well-established electromagnetic model to correctly explain the radar return from the image segments. It is applied to a series of five COSMO-SkyMed images regarding an event chosen as a test bed, i.e., a flood occurred in Northern Italy in 2009. In order to associate the segments to the classes of flooded or non-flooded areas, some reference multi-temporal backscattering trends have been assumed with the aid of the theoretical model. Using these reference trends as a training set, a classification algorithm has been developed to generate a map of the flood evolution. Although the methodology needs to be further tested on different case studies, our investigation demonstrates the feasibility and the utility of a combined use of an electromagnetic scattering model and an advanced image processing technique for inundation monitoring. | en |
dc.language.iso | English | en |
dc.relation.ispartof | Remote Sensing of Environment | en |
dc.relation.ispartofseries | /115 (2011) | en |
dc.subject | SAR | en |
dc.subject | segmentation | en |
dc.title | Flood monitoring using multi-temporal COSMO-SkyMed data: Image segmentation and signature interpretation | en |
dc.type | article | en |
dc.description.status | Published | en |
dc.type.QualityControl | Peer-reviewed | en |
dc.description.pagenumber | 990-1002 | en |
dc.subject.INGV | 05. General::05.08. Risk::05.08.02. Hydrogeological risk | en |
dc.identifier.doi | 10.1016/j.rse.2010.12.002 | en |
dc.description.obiettivoSpecifico | 1.10. TTC - Telerilevamento | en |
dc.description.journalType | JCR Journal | en |
dc.description.fulltext | reserved | en |
dc.contributor.author | Pulvirenti, L. | en |
dc.contributor.author | Chini, M. | en |
dc.contributor.author | Pierdicca, N. | en |
dc.contributor.author | Guerriero, L. | en |
dc.contributor.author | Ferrazzoli, P. | en |
dc.contributor.department | Sapienza University of Rome | en |
dc.contributor.department | Sapienza University of Rome | en |
dc.contributor.department | Tor Vergata University | en |
dc.contributor.department | Tor Vergata University | en |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.grantfulltext | reserved | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Sapienza University of Rome | - |
crisitem.author.dept | Luxembourg Institute of Science and Technology (LIST) | - |
crisitem.author.dept | Sapienza Università di Roma | - |
crisitem.author.dept | Tor Vergata University | - |
crisitem.author.dept | Tor Vergata University | - |
crisitem.classification.parent | 05. General | - |
Appears in Collections: | Article published / in press |
Files in This Item:
File | Description | Size | Format | Existing users please Login |
---|---|---|---|---|
2011_RSE_Pulvirenti_et_al.pdf | 2.89 MB | Adobe PDF |
WEB OF SCIENCETM
Citations
50
136
checked on Feb 7, 2021
Page view(s)
134
checked on Apr 17, 2024
Download(s)
43
checked on Apr 17, 2024