Bara'ah Qoqazeh

Ms. Bara'ah Qoqazeh

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 December 2022 in Forests
Verified
Journal Article
Open access
PDF file
BABassam M. Al-Qarallah
Bassam M. Al-Qarallah
YOYahia Othman
Yahia Othman
MAMalik G. Al-Ajlouni
Malik G. Al-Ajlouni
HAHadeel Al-heyari
Hadeel Al-heyari
BQBara'ah Qoqazeh
Bara'ah Qoqazeh
The objective of this study was to evaluate the separability potential of Sentinel-2A (MultiSpectral Instrument, MSI) and Landsat (Operational Land Imager, OLI and Thermal Infrared Sensor, TIRS) derived indices for detecting small-extent (70%. In fact, the dNBR-Sentinel-2/Landsat-8 overall accuracy and Kappa coefficient for classifying fire severity degree were less than 70% across the studied sites, except for Sentinel-dNBR in Dibbeen (72.5%). In conclusion, Sentinel-dNBR and Landsat promise to delimitate forest fire perimeters of small-scale (<25 ha) areas, but further remotely-sensed techniques are require (e.g., Landsat-Sentinel data fusion) to improve the fire severity-separability potential.