Go to  Advanced Search

Modeling approach for upscaling gross ecosystem production to the landscape scale using remote sensing data

Show full item record

Files in this item

Files Size Format Description   View
Black_AGU_2007JG000666.pdf 1.002Mb Adobe Portable Document Format   View/Open
 
Title: Modeling approach for upscaling gross ecosystem production to the landscape scale using remote sensing data
Author: Hilker, Thomas; Coops, Nicholas C.; Hall, Forrest G.; Black, T. Andrew; Chen, Baozhang; Krishnan, Praveena; Wulder, Michael A.; Sellers, Piers J.; Middleton, Elizabeth M.; Huemmrich, Karl F.
Issue Date: 2008-07
Publicly Available in cIRcle 2011-05-25
Publisher American Geophysical Union
Citation: Hilker, Thomas; Coops, Nicholas C; Hall, Forrest G; Black, T Andrew; Chen, Baozhang; Krishnan, Praveena; Wulder, Michael A; Sellers, Piers J; Middleton, Elizabeth M; Huemmrich, Karl F. 2008. Modeling approach for upscaling gross ecosystem production to the landscape scale using remote sensing data. Journal of Geophysical Research Biogeosciences 113 G03006 dx.doi.org/10.1029/2007JG000666
Abstract: Gross ecosystem production (GEP) can be estimated at the global scale and in a spatially continuous mode using models driven by remote sensing. Multiple studies have demonstrated the capability of high resolution optical remote sensing to accurately measure GEP at the leaf and stand level, but upscaling this relationship using satellite data remains challenging. Canopy structure is one of the complicating factors as it not only alters the strength of a measured signal depending on integrated leaf-angle-distribution and sun-observer geometry, but also drives the photosynthetic output and light-use-efficiency ( ɛ ) of individual leaves. This study introduces a new approach for upscaling multiangular canopy level reflectance measurements to satellite scales which takes account of canopy structure effects by using Light Detection and Ranging (LiDAR). A tower-based spectro-radiometer was used to observe canopy reflectances over an annual period under different look and solar angles. This information was then used to extract sunlit and shaded spectral end-members corresponding to minimum and maximum values of canopy- ɛ over 8-d intervals using a bidirectional reflectance distribution model. Using three-dimensional information of the canopy structure obtained from LiDAR, the canopy light regime and leaf area was modeled over a 12 km2 area and was combined with spectral end-members to derive high resolution maps of GEP. Comparison with eddy covariance data collected at the site shows that the spectrally driven model is able to accurately predict GEP (r 2 between 0.75 and 0.91, p < 0.05). An edited version of this paper was published by AGU. Copyright 2008 American Geophysical Union.
Affiliation: Land and Food Systems, Faculty of
URI: http://hdl.handle.net/2429/34815
Peer Review Status: Reviewed
Scholarly Level: Faculty

This item appears in the following Collection(s)

Show full item record

All items in cIRcle are protected by copyright, with all rights reserved.

UBC Library
1961 East Mall
Vancouver, B.C.
Canada V6T 1Z1
Tel: 604-822-6375
Fax: 604-822-3893