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We describe and validate an automated model that retrieves subpixel snow-covered area and effective grain size from Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) data. The model analyzes multiple endmember spectral mixtures with a spectral library of snow, vegetation, rock, and soil. We derive snow spectral endmembers of varying grain size from a radiative transfer model; spectra for vegetation, rock, and soil were collected in the field and laboratory. For three AVIRIS images of Mammoth Mountain, California that span common snow conditions for winter through spring, we validate the estimates of snow-covered area with fine-resolution aerial photographs and validate the estimates of grain size with stereological analysis of snow samples collected within 2 h of the AVIRIS overpasses. The RMS error for snowcovered area retrieved from AVIRIS for the combined set of three images was 4%. The RMS error for snow grain size retrieved from a 3 Â 3 window of AVIRIS data for the combined set of three images is 48 Am, and the RMS error for reflectance integrated over the solar spectrum and over all hemispherical reflectance angles is 0.018. D

Biological invasions contribute to global environmental change, but the dynamics and consequences of most invasions are difficult to assess at regional scales. We deployed an airborne remote sensing system that mapped the location and impacts of five highly invasive plant species across 221,875 ha of Hawaiian ecosystems, identifying four distinct ways that these species transform the three-dimensional (3D) structure of native rain forests. In lowland to montane forests, three invasive tree species replace native midcanopy and understory plants, whereas one understory invader excludes native species at the ground level. A fifth invasive nitrogen-fixing tree, in combination with a midcanopy alien tree, replaces native plants at all canopy levels in lowland forests. We conclude that this diverse array of alien plant species, each representing a different growth form or functional type, is changing the fundamental 3D structure of native Hawaiian rain forests. Our work also demonstrates how an airborne mapping strategy can identify and track the spread of certain invasive plant species, determine ecological consequences of their proliferation, and provide detailed geographic information to conservation and management efforts.biological invasion ͉ Hawaii ͉ imaging spectroscopy ͉ LiDAR ͉ tropical forest T he three-dimensional (3D) structure of forest canopies affects the distribution and absorption of solar radiation, the growth and recruitment of plants, and the use of forest resources by insects, birds, and mammals, including humans (1-6). Changes in canopy structure are obvious when forests are planted or cleared, but other structural changes are more difficult to assess. Invasive alien species contribute to environmental change by altering the composition and functioning of ecosystems (7-9), but many studies have documented only the local-scale spread of invasive plants into forests and their local consequences (10-13). The complexity and natural variability of forest ecosystems limit the extent to which local field studies can be used to characterize the regional-scale effects of biological invasions on forest structure and functioning.Remote sensing provides a synoptic view of ecosystems, but the location of invasive species in forests, much less their ecological consequences, has proven difficult to detect from satellite or aircraft sensors. Traditional aircraft measurements, such as digital photography, often fail to provide the spectral information needed to locate a particular species reliably (14). Satellite instruments are usually too coarse in spatial resolution, spectral information, or both. Resolving both the presence and the ecological impacts of invasive species requires specialized equipment and analytical approaches (15).We deployed an airborne remote sensing system designed to measure the composition, physiology, and structure of ecosystems. The Carnegie Airborne Observatory (CAO) integrates high-fidelity imaging spectrometers (HiFIS) with light detection and ranging (LiDAR) sensors for regional-sc...

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