文章基本信息

标题：Mapping Ground Cover Using Hyperspectral Remote Sensing after the 2003 Simi and Old Wildfires in Southern California
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作者：Sarah A. Lewis ; Leigh B. Lentile ; Andrew T. Hudak 等
期刊名称：Fire Ecology
出版年度：2007
卷号：3
期号：1
页码：109-128
DOI：10.4996/fireecology.0301109
摘要：Wildfire effects on the ground surface are indicative of the potential for post-fire watershed erosion response. Areas with remaining organic ground cover will likely experience less erosion than areas of complete ground cover combustion or exposed mineral soil. The Simi and Old fires burned ∼67,000 ha in southern California in 2003. Burn severity indices calculated from pre- and post-fire multispectral imagery were differenced (i.e., differenced Normalized Burn Ratio (dNBR)) to highlight fire-induced changes to soil and vegetation. Aerial and field hyperspectral data were also collected together with field ground cover measurements soon after the fires. Spectral endmembers representing green vegetation, nonphotosynthetic vegetation (NPV), charred NPV, and charred and uncharred inorganic materials (soil, ash, and rock) were used in a constrained linear spectral unmixing process to determine the post-fire fractional ground cover of each component on the ground surface. The spectral unmixing results, dNBR, and a Relative dNBR (RdNBR) were validated using field-measured fractional ground cover estimates to determine which product best predicted the conditions on the ground. The spectral unmixing results were significantly correlated to all classes of charred and uncharred organics and inorganics, and the dNBR was the best indicator of charred soil and green vegetation. The RdNBR had several significant correlations with the ground data, yet did not consistently correlate well with any specific ground cover types. A map of post-wildfire ground cover and condition, especially exposed soil and remaining vegetative cover, is a good indicator of the fire’s effect on the ground surface and the resulting potential for hydrologic response.
关键词：burn severity ; dNBR ; erosion potential ; hyperspectral data ; Relative dNBR ; southern California wildfires ; spectral mixture analysis