Department of Earth System Science, University of California, Irvine, CA, USA.
Earth System Science Program, Faculty of Natural Sciences, Universidad del Rosario, Bogota, Colombia.
Sci Data. 2022 May 30;9(1):249. doi: 10.1038/s41597-022-01343-0.
Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012-2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.
美国西部和其他火灾多发地区的野火频发给人类健康和生态系统功能带来了巨大风险。然而,由于缺乏系统量化火灾蔓延、行为和影响的数据产品,我们对野火行为的了解仍然有限。在这里,我们开发了一种新的基于对象的系统,用于使用 375m 可见红外成像辐射计套件主动火灾探测来跟踪单个火灾的进展。在每半个工作日的时间步长内,根据空间接近度对火灾像素进行聚类,要么将其附加到现有的主动火灾对象上,要么将其分配给新对象。这种自动系统允许我们在卫星数据采集后不久更新每个火灾事件的属性、划定火灾范围并识别活跃的火前线。使用该系统,我们绘制了 2012-2020 年加利福尼亚火灾的历史记录。我们的方法和数据流可能对火灾蔓延模型的校准和评估、实时野火排放的估计以及火灾预测模型初始条件的规定有用。