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Record Search Query: [Source_Name: Short_Name='AIRCRAFT']

Laser Vegetation Imaging Sensor (LVIS) Dataset over La Selva Biological Research Station and surrounding areas of Costa Rica such as Turrialba, Palo Verde, Santa Rosa and Arenal Volcano.
Entry ID: GSFC_LVIS_2005_CR_

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Summary
Abstract: NASA's Laser Vegetation Imaging Sensor (LVIS) has pioneered the use of waveform-based measurements since 1997. Images of sub-canopy topography, canopy height, canopy vertical structure and various parameters describing forest structure are routinely obtained using the system. In 2005, LVIS was used to image selected areas of Costa Rica, including Braulio Carillo National Park, La Selva Biological Station, the Turrialba area, Arenal volcano, and Palo Verde Biological Station.

The primary data products are:

* Earth topography (bare ground with vegetation removed).
* Vertical structure of tree canopies.
* Biomass estimates and above ground carbon stocks.
* Surface roughness.
* Entropy or Information density of the surveyed surface
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Platform
Aircraft Ancillary Description
Access Constraints While substantial efforts have been made to ensure the accuracy of data and documentation, complete accuracy of data sets can not be guaranteed. All data are made available "as is". The LVIS team can not assume responsibility for damages resulting from mis-use or mis-interpretation of datasets or from errors or omissions that may exist in the data. Data users are welcome to collaborate with the ... View entire text
Use Constraints See data use at the project home page.
Personnel
JAMES B BLAIR
Role: TECHNICAL CONTACT
Phone: 301-614-6741
Email: James.B.Blair at nasa.gov
Contact Address:
NASA
Goddard Space Flight Center
Mailstop 694.0
City: Greenbelt
Province or State: MD
Postal Code: 20771
Country: USA
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Publications/References
Blair, J. B., D. L. Rabine, and M. A. Hofton. 1999. The Laser Vegetation Imaging
Sensor: a medium-altitude, difitisation-only, airborne laser altimeter for mapping vegetation and topography. ISPRS Journal of Photogrammetry & Remote Sensing. 54: 115-122.
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