Paper
20 August 2009 NEON: the first continental-scale ecological observatory with airborne remote sensing of vegetation canopy biochemistry and structure
Author Affiliations +
Abstract
The National Ecological Observatory Network (NEON), being funded by the National Science Foundation, is a continental-scale research platform for discovering, understanding and forecasting the impacts of climate change, land-use change, and invasive species on ecology. Local site-based flux tower and field measurements will be coordinated with high resolution, regional airborne remote sensing observations. The NEON Airborne Observation Platform (AOP) consists of an aircraft platform carrying remote sensing instrumentation designed to achieve sub-meter to meter scale ground resolution to bridge scales from organism and stand scales to the scale of satellite based remote sensing. Data from the AOP will be openly available to the science community and will provide quantitative information on land use change, and changes in ecological structure and chemistry including the presence and effects of invasive species. Remote sensing instrumentation consists of an imaging spectrometer measuring surface reflectance over the continuous wavelength range from 400 to 2500 nm with 10 nm resolution, a scanning, small footprint waveform LiDAR for 3-D canopy structure measurements and a high resolution airborne digital camera. The AOP science objectives, key mission requirements, the conceptual design and development status are presented.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Brian R. Johnson, Thomas U. Kampe, Michele A. Kuester, and Michael Keller "NEON: the first continental-scale ecological observatory with airborne remote sensing of vegetation canopy biochemistry and structure", Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 745402 (20 August 2009); https://doi.org/10.1117/12.825697
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Cited by 3 scholarly publications.
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KEYWORDS
Neon

Sensors

Spectroscopy

Vegetation

LIDAR

Calibration

Climatology

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