Stanford, CAA lack of technology needed to explore and monitor vast regions of tropical rain forest has been a critical bottleneck for Earth scientists, conservationists, and forest managers. As a result, we have limited understanding of the composition and function of these forests and how they are responding to clearing, invasive plants, climate change, and other threats. Gregory Asner and his team at the Carnegie Institution's Department of Global Ecology recently created a new approach, part of the Carnegie Spectranomics Project, which can determine the chemical and structural properties and even the diversity of species in unprecedented detail over broad swaths of rain forests from aircraft. In a commitment to support this new science of airborne forest ecology, the Gordon and Betty Moore Foundation has awarded Asner a $5.2-million grant to advance the instrument technology required to make rain forest exploration and monitoring a reality.
The new technology is called High-fidelity Imaging Spectroscopy (HiFIS). It is part of the Carnegie Spectranomics Project and a major improvement of instrumentation already established aboard the Carnegie Airborne Observatory (CAO)a unique airborne mapping system that can inventory and probe rain forest vegetation over nearly 40,000 acres per day. The highly portable CAO is flown aboard a fixed-wing aircraft. It uses waveform LiDAR (light detection and ranging) system that maps the 3-dimensional structure of vegetation and combines it with spectroscopic imaging. By analyzing many wavelengths of reflected light, this imaging reveals a forest's biochemistry in stunningly beautiful 3-D maps. Although already pathbreaking and successful, the existing system lacks several critical features needed for the most detailed chemical and taxonomic mapping.
"Infrared reflectances of tropical forest canopies are often unique signatures for species," noted Asner. "This generous grant, combined with funds from other
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| Contact: Greg Asner gpa@ciw.edu 650-380-2828 Carnegie Institution Source:Eurekalert |
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