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HYPERSPECTRAL AND LIDAR REMOTE SENSING OF FIRE FUELS IN HAWAII VOLCANOES NATIONAL PARK
Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub‐montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non‐photosynthetic vegetation, and bare substrate and shade. Small‐footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three‐dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three‐dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three‐dimensional properties of ecosystems, their flammability, and the potential for fire spread.
HYPERSPECTRAL AND LIDAR REMOTE SENSING OF FIRE FUELS IN HAWAII VOLCANOES NATIONAL PARK
Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub‐montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non‐photosynthetic vegetation, and bare substrate and shade. Small‐footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three‐dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three‐dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three‐dimensional properties of ecosystems, their flammability, and the potential for fire spread.
HYPERSPECTRAL AND LIDAR REMOTE SENSING OF FIRE FUELS IN HAWAII VOLCANOES NATIONAL PARK
Varga, Timothy A. (author) / Asner, Gregory P. (author)
Ecological Applications ; 18 ; 613-623
2008-04-01
11 pages
Article (Journal)
Electronic Resource
English