Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/401
DC FieldValueLanguage
dc.contributor.authorMitri, Georgeen_US
dc.contributor.authorNasrallah, Georgyen_US
dc.contributor.authorGebrael, Karenen_US
dc.contributor.authorBeshara, Josephen_US
dc.contributor.authorNehme, Mayaen_US
dc.date.accessioned2020-12-23T08:29:44Z-
dc.date.available2020-12-23T08:29:44Z-
dc.date.issued2020-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/401-
dc.description.abstractAssessment of potential risk of land degradation, especially after fire events, is essential for identifying and prioritizing sites for post-fire management. This study aimed to model potential post-fire land degradation risk in Lebanon in order to plan and prioritize post-fire management actions. The specific objectives were to 1) map "burn severity" of the year 2019 using Landsat 8 and Sentinel 2-A imagery and 2) model post-fire land degradation risk using a Geographic ObjectBased Image Analysis (GEOBIA) approach. Initially, mapping burned areas of the 2019 fire season involved the use of a differenced Normalized Burn Ratio (dNBR) of Sentinel 2-A imagery. Another dNBR image was produced with the use of Landsat 8 imagery. Mapping overall burn severity was conducted based on cross-mapping between the two dNBR images which involved data sources of different spatial and spectral characteristics. Potential post-fire degradation risk was modelled in GEOBIA with the combined use of burn severity and topographic data (i.e., slope gradients). In addition, field data was collected to produce a Composite Burn Index (CBI) of fire-affected sites. The correlation between field data (i.e., CBI scores) and imagery analysis (i.e., dNBR data from Sentinel 2-A and Landsat 8) was assessed using a Spearman correlation test. The combined use of satellite remote sensing images (i.e., polygons of postfire degradation risk) and their corresponding ancillary data (i.e., CBI and soil texture) allowed the prioritization of fire affected sites for implementing post-fire restoration measures.en_US
dc.language.isoengen_US
dc.subjectEarth observing sensorsen_US
dc.subjectSoil scienceen_US
dc.subjectData modelingen_US
dc.subjectVegetationen_US
dc.subjectCompositesen_US
dc.subjectGeographic Information System (GIS)en_US
dc.subject.lcshImage analysisen_US
dc.subject.lcshImage segmentationen_US
dc.subject.lcshRemote sensingen_US
dc.titleAssessment of post-fire land degradation risk in Lebanon's 2019 fire affected areas using remote sensing and GISen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020) (8th : 16-18 March 2020 : Cyprus)en_US
dc.contributor.affiliationInstitute of Environmenten_US
dc.contributor.affiliationInstitute of Environmenten_US
dc.contributor.affiliationInstitute of Environmenten_US
dc.description.volume11524en_US
dc.date.catalogued2020-09-22-
dc.description.statusPublisheden_US
dc.identifier.OlibID271997-
dc.relation.ispartoftextSPIEen_US
dc.provenance.recordsourceOliben_US
Appears in Collections:Institute of Environment
Show simple item record

Record view(s)

4
checked on Dec 4, 2021

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.