Assessing Potential Safety Zone Suitability Using a New Online Mapping Tool

被引:14
作者
Campbell, Michael J. [1 ]
Dennison, Philip E. [1 ]
Thompson, Matthew P. [2 ]
Butler, Bret W. [3 ]
机构
[1] Univ Utah, Dept Geog, Salt Lake City, UT 84112 USA
[2] US Forest Serv, USDA, Rocky Mt Res Stn, Ft Collins, CO 80526 USA
[3] US Forest Serv, USDA, Rocky Mt Res Stn, Missoula, MT 59801 USA
来源
FIRE-SWITZERLAND | 2022年 / 5卷 / 01期
基金
美国国家科学基金会;
关键词
firefighter safety; safe separation distance; safety zones; LCES; Google Earth Engine; lidar; LANDFIRE; Landsat; GEDI; WILDLAND FIREFIGHTER SAFETY; UNITED-STATES; TRAVEL RATES; FIRE; SLOPE; LIDAR; FUEL; SUPPRESSION; VEGETATION; ACCURACY;
D O I
10.3390/fire5010005
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire's heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use.
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页数:24
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