一个可怕的野火季节将在2020年紧随一场大流行之后到来,这是完全合理的。9月份,北美发生了数十起大火,包括85起未被控制的大火和6起被控制的大火,大火遍及12个州。

活跃的火灾已经烧毁了300多万英亩的土地,今年迄今已经有41,417起火灾烧毁了近500万英亩的土地。此次火灾季节的严重程度将超过过去10年的平均水平。

更好地了解森林火灾

全球变暖是经常提到的一个贡献者野火,但也有其他的因素了。越来越多的研究人员正在寻找在地址申请新的方法野火的危险。它们包括工具,如深度学习和人工智能(AI),以更好地了解野火和控制它们的强度。

这个模型可以用来揭示最容易发生野火的地区

一种新的深度学习模型使用遥感和卫星数据跨12个西方国家微量燃料的水分含量,在效果跟踪容易可燃的植物材料的量和如何干它是。额外的测试完成后,该模型可以用来揭示风险最大的领域野火和计划用于规定烧伤最好的地区。由斯坦福大学ecohydrologist的带领下,研究结果发表在杂志环境遥感。

递归神经网络

该模型使用了来自美国林务局国家燃料湿度数据库的数据,该数据库从数千个样本中收集了植物水分信息。通过使用“循环神经网络”,该系统利用燃料湿度数据来验证可见光和来自空间传感器的微波雷达信号的测量值,这些传感器的任务是估算燃料湿度的测量值。

波长较长的新卫星可以对森林冠层深处的水分含量进行敏感的观测。来自模型的估计被用于生成交互式地图,消防机构可能有一天会使用这些地图来识别模式和优先进行野火控制估计。

研究人员还在努力分析更好、更有效的灭火措施对火灾规模和频率的影响。该理论认为:当消防员扑灭较小的植被火灾时,其结果是创造了一个野火更大或更频繁的环境。

自然再生循环

老的树木会自然地燃烧太阳的热量,为新生长的树木让路

该理论的前提是,野火对森林的周期性再生起着至关重要的作用。老的树木会自然地燃烧太阳的热量,为新生长的树木让路。然而,更有效的灭火措施可能会破坏自然循环,并与全球变暖一起,加剧更大规模、更频繁的火灾发生的可能性。

在WiFire实验室在加利福尼亚州和加拿大阿尔伯塔大学的研究人员正在使用人工智能(AI)来分析环境和规定烧伤,可以拯救森林的某些部分不与再生的自然循环的干扰提供建议。

提供野火的早期预警

设备操作由太平洋天然气和电力公司(PG&E)造成2018的篝火,在加利福尼亚州历史上最具破坏性野火。由于引发野火的威胁,PG&E今年切断电源,以172000级的客户在北加州的劳动节周末,例如。一个问题是风拆除电源线或投掷杂物放进去的威胁。南加州爱迪生公司(SCE),其他实用程序,警告说,约55,000个客户账户可能会失去动力。

加州公用事业公司SCE, PG&E和圣地亚哥燃气电力公司正在帮助资助加利福尼亚的火灾预警摄像机网络,这将有助于提供火灾的早期预警。摄像机监视着美国西部的五处地区,以提供早期预警,而且摄像机的数量正在迅速增加。

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一个加州野火的起源是一个性别显示党

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确保“消防员的健康”包括设备的清洁
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