Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Canada.
Stat Methods Med Res. 2011 Apr;20(2):131-56. doi: 10.1177/0962280210372454. Epub 2010 Oct 1.
Obtaining accurate measures of exposure to forest fire smoke is important for the assessment of health risk. Estimating exposure from air quality monitors is challenging because of the sparseness of the monitoring networks in remote areas. However, satellite imagery offers a novel and data-rich tool to provide visual information on smoke plumes. We will discuss statistical techniques for obtaining estimates of forest fire smoke plumes using classification algorithms on data from satellite imagery in order to develop automated processes for identifying exposure. The aim is to identify whether such methods may offer a high-resolution approach that provides a reliable estimate of smoke and a more thorough caption of the spatial distribution of smoke from fires than is currently available.
获取森林火灾烟雾暴露的准确测量值对于评估健康风险非常重要。由于偏远地区空气质量监测网络的稀疏性，从空气质量监测器估计暴露量具有挑战性。然而，卫星图像提供了一种新颖的数据丰富工具，可以提供烟雾羽流的视觉信息。我们将讨论使用卫星图像数据上的分类算法获取森林火灾烟雾羽流估计值的统计技术，以便开发用于识别暴露的自动化过程。目的是确定这些方法是否可以提供一种高分辨率的方法，该方法可以可靠地估计烟雾，并更全面地描述火灾产生的烟雾的空间分布，而目前尚无法实现。
