Early Adopters

Drylands cover approximately 40% of Earth’s terrestrial surface, support nearly 35% of the globe’s population, and have the largest net change in population compared to other ecosystems (Millennium Ecosystem Assessment, MEA, 2005). Population growth, coupled with low levels of human well-being, food security, land degradation, and ecosystem service vulnerability in dryland ecosystems are major global concerns. Among dryland subtypes, semiarid areas are the most vulnerable to loss of ecosystem services (MEA, 2005). In the semiarid western US, the distribution of species and vegetation types are expected to shift in response to climate change and other stressors. Previous studies have documented the change in fire regimes and the increasing fire-invasive grass cycle occurring in the western U.S. The change in vegetation composition and structure due to stressors such as climate change, fire, and invasive species, alter the fuel load making these ecosystems vulnerable to high-severity fire. Quantifying the composition and structural variability of short-statured semiarid vegetation (e.g. shrublands, annual grasses) is necessary for long-term land management and understanding ecosystem vulnerability. The composition and structural variability of semiarid vegetation can be captured leveraging synergistic remote sensing data, such as from hyperspectral and laser altimetry systems. As early adopters of ICESat-2, our objective is to explore the potential of ICESat-2, either independently or with data fusion of hyperspectral and multispectral data, to quantify aboveground biomass of semiarid ecosystem vegetation. Our goal is to use estimates of biomass to quantify carbon, fuel loads, and monitor change in regions such as the Great Basin, western U.S.