Evaluating post-fire recovery of Latroon dry forest using Landsat ETM+, unmanned aerial vehicle and field survey data

Bassam Qarallah; Malik Al-Ajlouni; Ayman Al-Awasi; Mohammad Alkarmy; Emad Al-Qudah; Ahmad Bani Naser; Amani Al-Assaf; C.M. Gevaert; Y. Al Asmar; M. Belgiu; Yahia A. Othman

doi:10.1016/j.jaridenv.2021.104587

Evaluating post-fire recovery of Latroon dry forest using Landsat ETM+, unmanned aerial vehicle and field survey data

Bassam Qarallah, Malik Al-Ajlouni, Ayman Al-Awasi, Mohammad Alkarmy, Emad Al-Qudah, Ahmad Bani Naser, Amani Al-Assaf, C.M. Gevaert, Y. Al Asmar, M. Belgiu, Yahia A. Othman^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

We evaluated the fire severity and recovery process of the Latroon dry forest in Jordan following the 2003 fire. A series of multi-temporal Landsat-ETM + data and the delta normalized burn ratio (dNBR) were used to map the fire severity immediately following the fire and 1,5,9,13 and 17 years after. In addition, combined field morpho-physiological measurements, unmanned aerial vehicle (UAV) were also used in 2020 to assess the forest recovery. Landsat-dNBR images revealed that about 65% of the forest was burned in 2003. In 2020, about 90% of the burned area recovered to condition before fire. UAV means were similar to ground measurement data across the severity classes and over the tested species. Landsat-dNBR images showed that most moderate and highly severe burned area in 2003 had recovered in 2020 but ground measurements showed that the severely burned area trees were significantly shorter (p

Original language	English
Article number	104587
Pages (from-to)	1-10
Number of pages	10
Journal	Journal of arid environments
Volume	193
Early online date	5 Jul 2021
DOIs	https://doi.org/10.1016/j.jaridenv.2021.104587
Publication status	Published - Oct 2021

Keywords

Remote sensing
Forest fires
dNBR
Drones
UAV
ITC-ISI-JOURNAL-ARTICLE
2024 OA procedure

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.jaridenv.2021.104587

ArticleFinal published version, 6.47 MBLicence: Taverne

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Qarallah, B., Al-Ajlouni, M., Al-Awasi, A., Alkarmy, M., Al-Qudah, E., Naser, A. B., Al-Assaf, A., Gevaert, C. M., Al Asmar, Y., Belgiu, M., & Othman, Y. A. (2021). Evaluating post-fire recovery of Latroon dry forest using Landsat ETM+, unmanned aerial vehicle and field survey data. Journal of arid environments, 193, 1-10. Article 104587. https://doi.org/10.1016/j.jaridenv.2021.104587

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title = "Evaluating post-fire recovery of Latroon dry forest using Landsat ETM+, unmanned aerial vehicle and field survey data",

abstract = "We evaluated the fire severity and recovery process of the Latroon dry forest in Jordan following the 2003 fire. A series of multi-temporal Landsat-ETM + data and the delta normalized burn ratio (dNBR) were used to map the fire severity immediately following the fire and 1,5,9,13 and 17 years after. In addition, combined field morpho-physiological measurements, unmanned aerial vehicle (UAV) were also used in 2020 to assess the forest recovery. Landsat-dNBR images revealed that about 65% of the forest was burned in 2003. In 2020, about 90% of the burned area recovered to condition before fire. UAV means were similar to ground measurement data across the severity classes and over the tested species. Landsat-dNBR images showed that most moderate and highly severe burned area in 2003 had recovered in 2020 but ground measurements showed that the severely burned area trees were significantly shorter (p ",

keywords = "Remote sensing, Forest fires, dNBR, Drones, UAV, ITC-ISI-JOURNAL-ARTICLE, 2024 OA procedure",

author = "Bassam Qarallah and Malik Al-Ajlouni and Ayman Al-Awasi and Mohammad Alkarmy and Emad Al-Qudah and Naser, {Ahmad Bani} and Amani Al-Assaf and C.M. Gevaert and {Al Asmar}, Y. and M. Belgiu and Othman, {Yahia A.}",

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Qarallah, B, Al-Ajlouni, M, Al-Awasi, A, Alkarmy, M, Al-Qudah, E, Naser, AB, Al-Assaf, A, Gevaert, CM , Al Asmar, Y , Belgiu, M & Othman, YA 2021, 'Evaluating post-fire recovery of Latroon dry forest using Landsat ETM+, unmanned aerial vehicle and field survey data', Journal of arid environments, vol. 193, 104587, pp. 1-10. https://doi.org/10.1016/j.jaridenv.2021.104587

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T1 - Evaluating post-fire recovery of Latroon dry forest using Landsat ETM+, unmanned aerial vehicle and field survey data

AU - Qarallah, Bassam

AU - Al-Ajlouni, Malik

AU - Al-Awasi, Ayman

AU - Alkarmy, Mohammad

AU - Al-Qudah, Emad

AU - Naser, Ahmad Bani

AU - Al-Assaf, Amani

AU - Gevaert, C.M.

AU - Al Asmar, Y.

AU - Belgiu, M.

AU - Othman, Yahia A.

PY - 2021/10

Y1 - 2021/10

N2 - We evaluated the fire severity and recovery process of the Latroon dry forest in Jordan following the 2003 fire. A series of multi-temporal Landsat-ETM + data and the delta normalized burn ratio (dNBR) were used to map the fire severity immediately following the fire and 1,5,9,13 and 17 years after. In addition, combined field morpho-physiological measurements, unmanned aerial vehicle (UAV) were also used in 2020 to assess the forest recovery. Landsat-dNBR images revealed that about 65% of the forest was burned in 2003. In 2020, about 90% of the burned area recovered to condition before fire. UAV means were similar to ground measurement data across the severity classes and over the tested species. Landsat-dNBR images showed that most moderate and highly severe burned area in 2003 had recovered in 2020 but ground measurements showed that the severely burned area trees were significantly shorter (p

AB - We evaluated the fire severity and recovery process of the Latroon dry forest in Jordan following the 2003 fire. A series of multi-temporal Landsat-ETM + data and the delta normalized burn ratio (dNBR) were used to map the fire severity immediately following the fire and 1,5,9,13 and 17 years after. In addition, combined field morpho-physiological measurements, unmanned aerial vehicle (UAV) were also used in 2020 to assess the forest recovery. Landsat-dNBR images revealed that about 65% of the forest was burned in 2003. In 2020, about 90% of the burned area recovered to condition before fire. UAV means were similar to ground measurement data across the severity classes and over the tested species. Landsat-dNBR images showed that most moderate and highly severe burned area in 2003 had recovered in 2020 but ground measurements showed that the severely burned area trees were significantly shorter (p

KW - Remote sensing

KW - Forest fires

KW - dNBR

KW - Drones

KW - UAV

KW - ITC-ISI-JOURNAL-ARTICLE

KW - 2024 OA procedure

U2 - 10.1016/j.jaridenv.2021.104587

DO - 10.1016/j.jaridenv.2021.104587

M3 - Article

SN - 0140-1963

VL - 193

SP - 1

EP - 10

JO - Journal of arid environments

JF - Journal of arid environments

M1 - 104587

ER -

Evaluating post-fire recovery of Latroon dry forest using Landsat ETM+, unmanned aerial vehicle and field survey data

Abstract

Keywords

UN SDGs

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