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Synthetic RapidEye data used for the detection of area-based spruce tree mortality induced by bark beetles

机译:合成RapidEye数据用于检测由树皮甲虫引起的基于面积的云杉树死亡率

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Tree mortality caused by outbreaks of the bark beetle Ips typographus (L.) plays an important role in the natural dynamics of Norway spruce (Picea abies L.) stands, which could cause far-reaching changes in the occurrence and duration of vegetation phenology. Field-based early detection of tree disturbances is hampered by logistic, terrain, and technical shortcomings, and by the inability to continuously monitor disturbances over large areas. Despite achievements in remote mapping of bark-beetle-induced tree mortalities, early warning has been mostly unsuccessful mainly because of the lack of spectral sensitivity and discrepancies in definitions of field- and image-based disturbance classes. Here we applied a method based on inter-annual phenology of Norway spruce stands derived from synthetic multispectral data to part of the Bavarian Forest National Park in Germany. We fused temporally continuous Moderate Resolution Imaging Spectroradiometer and discrete RapidEye data using a flexible spatiotemporal data fusion method to achieve validated 8-day RapidEye-like composites of normalized difference vegetation index for 2011. We assumed that the dead trees delineated on 2012 aerial photographs were those in which bark beetle infestations were initiated in 2011. Samples were drawn with variable-sized buffering to represent the areas prone to infestations and their surroundings. We applied a conditional inference random forest to select the best image date among the entire 46 synthetic datasets to best discriminate between the core infestation patches and their surroundings from the subsequent year. Of the discrete time points identified, day 281 of the year represented the highest discrepancy between aerial image-based dead trees and their surroundings. Classification results were significantly correlated with beetle count data obtained using pheromone traps. Our method provided valuable information for management purposes and enabled wall-to-wall mapping of stands prone to infestation and its uncertainty. The results offer potential implications for rapid and cost-effective monitoring of bark beetle outbreaks using satellite data, which would be of great benefit for both management and research tasks.
机译:由树皮甲虫Ips typographus(L.)爆发引起的树木死亡率在挪威云杉(Picea abies L.)林分的自然动态中起重要作用,这可能会导致植被物候发生和持续时间发生深远的变化。后勤,地形和技术缺陷,以及无法连续监视大面积干扰,阻碍了基于现场的树木干扰早期检测。尽管在树皮甲虫致死率的远程制图方面取得了成就,但预警主要是不成功的,主要是因为缺乏光谱敏感性以及基于场和图像的干扰类别定义方面的差异。在这里,我们将基于挪威云杉林的年际物候的方法应用到了德国巴伐利亚森林国家公园的一部分,该方法是从合成的多光谱数据中得出的挪威云杉林的。我们使用灵活的时空数据融合方法将时间连续的中等分辨率成像光谱仪与离散的RapidEye数据融合,以实现经过验证的2011年标准化植被差指数的8天类似RapidEye的合成物。我们假设在2012年航拍照片上描绘的枯树是那些其中在2011年启动了树皮甲虫侵扰。使用可变大小的缓冲液抽取样本,以表示容易受到侵扰的区域及其周围环境。我们应用条件推断随机森林在整个46个合成数据集中选择最佳影像日期,以最佳地区分核心侵袭斑块及其后一年的周围环境。在确定的离散时间点中,一年中的第281天代表了基于航空影像的枯树与其周围环境之间的最大差异。分类结果与使用信息素陷阱获得的甲虫计数数据显着相关。我们的方法为管理目的提供了有价值的信息,并能够对易于出没及其不确定性的展台进行逐壁映射。结果为利用卫星数据快速,经济高效地监测树皮甲虫暴发提供了潜在的启示,这将对管理和研究工作均大有裨益。

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