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 journalArticleAcademicpeer-review

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 languageEnglish
Article number104587
Pages (from-to)1-10
Number of pages10
JournalJournal of arid environments
Volume193
Early online date5 Jul 2021
DOIs
Publication statusE-pub ahead of print/First online - 5 Jul 2021

Keywords

  • Remote sensing
  • Forest fires
  • dNBR
  • Drones
  • UAV
  • ITC-ISI-JOURNAL-ARTICLE

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