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

编号 030033804

推送时间 20220411

研究领域 森林经理 

年份 2022 

类型 期刊 

语种 英语

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

来源期刊 JOURNAL OF ARID ENVIRONMENTS

期 第338期

发表时间 20210605

关键词 Remote sensing;  Forest fires;  dNBR;  Drones;  UAV;  Pinus; 

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.

服务人员 付贺龙

服务院士 唐守正

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