Barber Quinn E, Jain Piyush, Whitman Ellen, Thompson Dan K, Guindon Luc, Parks Sean A, Wang Xianli, Hethcoat Matthew G, Parisien Marc-André
Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122 Street NW, Edmonton, AB, T6H 3S5, Canada.
Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, 1219 Queen Street, Sault Ste. Marie, ON, P6A 2E5, Canada.
Sci Data. 2024 Jul 11;11(1):764. doi: 10.1038/s41597-024-03436-4.
Satellite data are effective for mapping wildfires, particularly in remote locations where monitoring is rare. Geolocated fire detections can be used for enhanced fire management and fire modelling through daily fire progression mapping. Here we present the Canadian Fire Spread Dataset (CFSDS), encompassing interpolated progressions for fires >1,000 ha in Canada from 2002-2021, representing the day-of-burning and 50 environmental covariates for every pixel. Day-of-burning was calculated by ordinary kriging of active fire detections from the Moderate Resolution Imaging Spectroradiometer and the Visible Infrared Imaging Radiometer Suite, enabling a substantial improvement in coverage and resolution over existing datasets. Day of burning at each pixel was used to identify environmental conditions of burning such as daily weather, derived weather metrics, topography, and forest fuels characteristics. This dataset can be used in a broad range of research and management applications, such as retrospective analysis of fire spread, as a benchmark dataset for validating statistical or machine-learning models, and for forecasting the effects of climate change on fire activity.
卫星数据对于绘制野火地图很有效,尤其是在监测稀少的偏远地区。地理定位的火灾探测可通过每日火灾蔓延制图用于加强火灾管理和火灾建模。在此,我们展示了加拿大火灾蔓延数据集(CFSDS),它包含了2002年至2021年加拿大境内面积超过1000公顷火灾的插值进展情况,代表了每个像素的燃烧日以及50个环境协变量。燃烧日是通过对中分辨率成像光谱仪和可见红外成像辐射仪套件的活跃火灾探测进行普通克里金法计算得出的,与现有数据集相比,在覆盖范围和分辨率方面有了显著提高。每个像素的燃烧日用于识别燃烧时的环境条件,如每日天气、衍生的气象指标、地形和森林燃料特征。该数据集可用于广泛的研究和管理应用,如火灾蔓延的回顾性分析、作为验证统计或机器学习模型的基准数据集,以及预测气候变化对火灾活动的影响。