title: Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.
abstract: 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.
authors.affiliation: Earth Systems Program, Stanford University, 397 Panama Mall, Stanford, California 94305, USA.
authors.forename: Timothy A
authors.initials: TA
authors.lastname: Varga
authors.forename: Gregory P
authors.initials: GP
authors.lastname: Asner
mesh_terms: D003247:Conservation of Natural Resources; D017753:Ecosystem; D005390:Fires; D006254:Hawaii; D021621:Imaging, Three-Dimensional; D018521:Plant Physiological Phenomena; D006109:Poaceae