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

被引:11
|
作者
Qarallah, Bassam [1 ]
Al-Ajlouni, Malik [1 ]
Al-Awasi, Ayman [2 ]
Alkarmy, Mohammad [2 ]
Al-Qudah, Emad [3 ]
Naser, Ahmad Bani [2 ]
Al-Assaf, Amani [4 ]
Gevaert, Caroline M. [5 ]
Al Asmar, Yolla [5 ]
Belgiu, Mariana [5 ]
Othman, Yahia A. [1 ]
机构
[1] Univ Jordan, Dept Hort & Crop Sci, Amman 11942, Jordan
[2] Minist Agr, Dept Forestry, Jerash, Jordan
[3] Minist Agr, Land & Irrigat Dept, Amman, Jordan
[4] Univ Jordan, Dept Agr Econ & Agribusiness, Amman 11942, Jordan
[5] Univ Twente, Fac Geo Informat Sci & Earth Observat, NL-7522 NB Enschede, Netherlands
关键词
Remote sensing; Forest fires; dNBR; Drones; UAV; Pinus; SURFACE REFLECTANCE DATA; BURN SEVERITY; SPECTRAL INDEXES; FIRE SEVERITY; MOISTURE STATUS; PECAN ORCHARDS; PERFORMANCE; CLIMATE;
D O I
10.1016/j.jaridenv.2021.104587
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
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 morphophysiological 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 < 0.001) than those from the moderate severity across the studied species. Therefore, Landsat-dNBR did not detect tree height changes. While UAV can potentially estimate the tree height, Landsat-ETM+ (near-infrared, chlorophyll; shortwave-infrared, water status) hold promise for estimating the physiology of the canopy. Overall, different remote sensing levels are required to track different kinds of changes in the recovered forests.
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页数:10
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