Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30741
DC FieldValueLanguage
dc.contributor.authorAdam, Mariana-
dc.contributor.authorFragkos, Konstantinos-
dc.contributor.authorSolomos, Stavros-
dc.contributor.authorBelegante, Livio-
dc.contributor.authorAndrei, Simona-
dc.contributor.authorTalianu, Camelia L.-
dc.contributor.authorMarmureanu, Luminita-
dc.contributor.authorAntonescu, Bogdan-
dc.contributor.authorEne, Dragos-
dc.contributor.authorNicolae, Victor-
dc.contributor.authorAmiridis, Vassilis-
dc.date.accessioned2023-11-06T08:34:00Z-
dc.date.available2023-11-06T08:34:00Z-
dc.date.issued2022-10-01-
dc.identifier.citationRemote Sensing, 2022, vol 14, iss. 19en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14279/30741-
dc.description.abstractLidar measurements of 11 smoke layers recorded at Măgurele, Romania, in 2014, 2016, and 2017 are analyzed in conjunction with the vegetation type of the burned biomass area. For the identified aerosol pollution layers, the mean optical properties and the intensive parameters in the layers are computed. The origination of the smoke is estimated by the means of the HYSPLIT dispersion model, taking into account the location of the fires and the injection height for each fire. Consequently, for each fire location, the associated land cover type is acquired by satellite-derived land cover products. We explore the relationship between the measured intensive parameters of the smoke layers and the respective land cover of the burned area. The vegetation type for the cases we analyzed was either broadleaf crops or grasses/cereals. Overall, the intensive parameters are similar for the two types, which can be associated with the fact that both types belong to the broader group of agricultural crops. For the cases analyzed, the smoke travel time corresponding to the effective predominant vegetation type is up to 2.4 days.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofRemote Sensingen_US
dc.rights© by the authorsen_US
dc.subjectbiomass burningen_US
dc.subjectERA5en_US
dc.subjectFLEXPARTen_US
dc.subjectHYSPLITen_US
dc.subjectland coveren_US
dc.subjectlidaren_US
dc.subjectMODISen_US
dc.titleMethodology for Lidar Monitoring of Biomass Burning Smoke in Connection with the Land Coveren_US
dc.typeArticleen_US
dc.collaborationNational Institute of Research and Development for Optoelectronics INOE 2000en_US
dc.collaborationERATOSTHENES Centre of Excellenceen_US
dc.collaborationAcademy of Athensen_US
dc.collaborationNational Observatory of Athensen_US
dc.subject.categoryNATURAL SCIENCESen_US
dc.subject.categoryENGINEERING AND TECHNOLOGYen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsOpen Accessen_US
dc.countryCyprusen_US
dc.countryGreeceen_US
dc.countryRomaniaen_US
dc.subject.fieldNatural Sciencesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3390/rs14194734en_US
dc.identifier.scopus2-s2.0-85139912905en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85139912905en
dc.contributor.orcid0000-0002-9237-8320en
dc.contributor.orcid0000-0002-3009-2407en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid0000-0002-4615-7623en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid0000-0001-8151-2304en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid0000-0001-5266-0930en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.relation.issue19en_US
dc.relation.volume14en_US
cut.common.academicyear2022-2023en_US
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.languageiso639-1en-
crisitem.journal.journalissn2072-4292-
crisitem.journal.publisherMDPI-
crisitem.author.orcid0000-0002-3009-2407-
crisitem.author.orcid0000-0001-5266-0930-
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