Use of random forests for modeling and mapping forest canopy fuels for fire behavior analysis in Lassen Volcanic National Park, California, USA

被引:60
作者
Pierce, Andrew D. [1 ,3 ]
Farris, Calvin A.
Taylor, Alan H. [1 ,2 ]
机构
[1] Penn State Univ, Dept Geog, University Pk, PA 16802 USA
[2] Penn State Univ, Earth & Environm Syst Inst, University Pk, PA 16802 USA
[3] Univ Hawaii, Dept Nat Resources & Environm Management, Manoa Honolulu, HI 96822 USA
基金
美国国家科学基金会;
关键词
Canopy fuels; Fuels mapping; Random Forest; Fire behavior modeling; Remote sensing; LAND FIRE; SIERRA-NEVADA; LANDSCAPE; SEVERITY; CLASSIFICATION; MOUNTAINS; REGIMES; LIDAR; SUPPRESSION; PATTERNS;
D O I
10.1016/j.foreco.2012.05.010
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Fire managers often need data that is spatially explicit at a fine scale (30 m) but is also laborious and time consuming to collect. This study integrates Landsat 5 imagery and topographic information with plot and tree based data to model and map four key canopy fuels variables: Canopy Bulk Density (CBD), Canopy Cover (CC), Canopy Base Height (CBH), and canopy Height (HT). We sampled 223 plots of 500 m(2) each in Lassen Volcanic National Park. Within each plot we recorded every tree by species, diameter, condition, and canopy position. Additionally, we measured each tree's height, height to live crown base and height to dead crown base. Finally, we took three hemispherical photographs of the forest canopy above each plot. We developed five topographic variables-elevation, slope, aspect, and two measures of topographic position-and used Landsat 5 spectral bands 1-5, and 7 as well as the Normalized Difference Vegetation Index (NDVI) and the Tasseled Cap Greenness, Brightness, and Wetness to model and then predict these canopy fuels variables for both 2009 and 2003 across LVNP. RF models relating predictor variables to canopy fuels characteristics had pseudo-r(2) values ranging from 0.55 to 0.68. To demonstrate the potential utility of our mapping procedure, we used our 2003 canopy fuels map along with a previously unpublished contemporary surface fuels map and the fire behavior modeling program FlamMap (R) to relate predicted fire behavior of our fuels maps with fire severity from the Monitoring Trends in Burn Severity (MTBS) dataset for the Bluff (2004) fire. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:77 / 89
页数:13
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