Analysis of sapling density regeneration in Yellowstone National Park with hyperspectral remote sensing data

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• 作者：Christopher Potter^a ; ^{Chris.Potter@nasa.gov} ; Shuang Li^a ; ^b ; Shengli Huang^a ; ^c ; Robert L. Crabtree^c ; ^d
• 关键词：Sapling density ; Post-fire ecosystems ; AVIRIS ; Hyperspectral ; Fire ecology ; Northern Rocky Mountains ; Yellowstone National Park
• 刊名：Remote Sensing of Environment
• 出版年：2012
• 出版时间：June, 2012
• 年：2012
• 卷：121
• 期：Complete
• 页码：61-68
• 全文大小：1231 K

文摘

The density of lodgepole pine (Pinus contorta) sapling regeneration was mapped in areas burned during the 1988 wildfires across Yellowstone National Park (YNP), Wyoming, USA. Hyperspectral image analysis and field measurements were combined across the entire YNP extent. Airborne Visible Infrared Imaging Spectrometer (AVIRIS) image data from 2006 were used to compute ten different vegetation indices (VI). The ten VIs were combined to build multiple regression models for predicting and mapping post-fire sapling density. Four different forms of regression modeling were applied to derive the highest possible prediction accuracy (correlation coefficient of R² = 0.83). Pine sapling regeneration 19 years after large-scale wildfires showed a high level of variability in patch density (ranging from 14/100 ha to 57/100 ha), whereas sapling density measured previously from the first decade following wildfire was more uniform (10/100 ha to 21/100 ha). The ecosystem-level clumpiness index showed major shifts in aggregation of different sapling density classes, and was consistent with an overall decrease in estimated sapling density of nearly 50 % between 1998 and 2007. This analysis revealed important succession patterns and processes in post-fire forest regeneration for the Greater Yellowstone Area (GYA).