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NEON: the first continental-scale ecological observatory with airborne remote sensing of vegetation canopy biochemistry and structureAuthor(s): Thomas U. Kampe; Brian R. Johnson; Michele Kuester; Michael Keller
Source: Journal of Applied Remote Sensing. 4(043510). DOI: 10.1117/1.3361375.
Publication Series: Scientific Journal (JRNL)
Station: International Institute of Tropical Forestry
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DescriptionThe National Ecological Observatory Network (NEON) is an ecological observation platform for discovering, understanding and forecasting the impacts of climate change, land use change, and invasive species on continental-scale ecology. NEON will operate for 30 years and gather long-term data on ecological response changes and on feedbacks with the geosphere, hydrosphere, and atmosphere. Local ecological measurements at sites distributed within 20 ecoclimatic domains across the contiguous United States, Alaska, Hawaii, and Puerto Rico will be coordinated with high resolution, regional airborne remote sensing observations. The Airborne Observation Platform (AOP) is an aircraft platform carrying remote sensing instrumentation designed to achieve sub-meter to meter scale ground resolution, bridging scales from organisms and individual stands to satellite based remote sensing. AOP instrumentation consists of a VIS/SWIR imaging spectrometer, a scanning small-footprint waveform LiDAR for 3-D canopy structure measurements and a high resolution airborne digital camera. AOP data will be openly available to scientists and will provide quantitative information on land use change and changes in ecological structure and chemistry including the presence and effects of invasive species. AOP science objectives, key mission requirements, and development status are presented including an overview of near-term risk-reduction and prototyping activities.
CitationKampe, Thomas U.; Johnson, Brian R.; Kuester, Michele; Keller, Michael. 2010. NEON: the first continental-scale ecological observatory with airborne remote sensing of vegetation canopy biochemistry and structure. Journal of Applied Remote Sensing. 4(043510). DOI: 10.1117/1.3361375.
KeywordsRemote sensing, ecology, vegetation structure, imaging spectroscopy, waveform LiDAR.
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