首页> 外文期刊>Journal of Applied Remote Sensing >Combining land surface temperature and shortwave infrared reflectance for early detection of mountain pine beetle infestations in western Canada
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Combining land surface temperature and shortwave infrared reflectance for early detection of mountain pine beetle infestations in western Canada

机译:结合地表温度和短波红外反射率,以早期发现加拿大西部的山松甲虫

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The current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak, which began in 1999, continues to be the leading cause of pine tree mortality in British Columbia. Information regarding the location and spatial extent of the current attack is required for mitigating practices and forest inventory updates. This information is available from spaceborne observations. Unfortunately, the monitoring of the mountain pine beetle outbreak using remote sensing is usually limited to the visible stage at which the expansion of the attack beyond its initial hosts is unpreventable. The disruption of the sap flow caused by a blue-staining fungi carried by the beetles leads to: 1. a decrease in the amount of liquid water stored in the canopy, 2. an increase in canopy temperature, and 3. an increase in shortwave infrared reflectance shortly after the infestation. As such, the potential for early beetle detection utilizing thermal remote sensing is possible. Here we present a first attempt to detect a mountain pine beetle attack at its earliest stage (green attack stage when the foliage remains visibly green after the attack) using the temperature condition index (TCI) derived from Landsat ETM+ imagery over an affected area in British Columbia. The lack of detailed ground survey data of actual green attack areas limits the accuracy of this research. Regardless, our results show that TCI has the ability to differentiate between affected and unaffected areas in the green attack stage, and thus it provides information on the possible epicenters of the attack and on the spatial extent of the outbreak at later stages (red attack and gray attack). Furthermore, we also developed a moisture condition index (MCI) using both shortwave infrared and thermal infrared measurements. The MCI index is shown to be more effective than TCI in detecting the green attack stage and provides a more accurate picture of beetle spread patterns.
机译:始于1999年的目前的山松甲虫(Dendroctonus tankerosae Hopkins)疫情仍然是不列颠哥伦比亚省松树死亡的主要原因。缓解做法和森林清单更新需要有关当前攻击的位置和空间范围的信息。该信息可从星载观测获得。不幸的是,使用遥感监测山松甲虫的爆发通常仅限于可见阶段,在该阶段无法防止攻击扩大到其最初的宿主。甲虫携带的蓝染真菌引起的汁液流动中断导致:1.冠层中储存的液态水量减少,2.冠层温度升高,以及3.短波升高出没后不久的红外反射率。这样,利用热遥感进行早期甲虫检测的潜力是可能的。在此,我们首次尝试使用源自Landsat ETM +影像的英国受灾地区的温度条件指数(TCI)来检测山松甲虫的最早阶段(绿色发作阶段,此时叶子在发作后仍保持明显绿色)。哥伦比亚。缺乏实际绿色攻击区域的详细地面调查数据限制了这项研究的准确性。无论如何,我们的结果表明,TCI能够在绿色攻击阶段区分受影响和未受影响的区域,因此,它可以提供有关攻击的可能震中和后期爆发的空间范围(红色攻击和灰色攻击)。此外,我们还利用短波红外和热红外测量技术开发了湿度条件指数(MCI)。在检测绿色攻击阶段时,MCI指数显示出比TCI更有效,并提供了更准确的甲虫传播方式图。

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