DocumentCode
576447
Title
On the relationship between nominal light use efficiency and leaf chlorophyll
Author
Schull, Mitchell ; Anderson, Martha ; Houborg, Rasmus ; Kustas, William
Author_Institution
Hydrol. & Remote Sensing Lab., USDA-ARS, Beltsville, MD, USA
fYear
2012
fDate
22-27 July 2012
Firstpage
7306
Lastpage
7308
Abstract
A light-use-efficiency (LUE)-based model of canopy resistance has been embedded into a thermal-based Two-Source Energy Balance (TSEB) model to facilitate coupled simulations of transpiration and carbon assimilation. The model assumes that deviations of the observed canopy LUE from a nominal stand-level value (LUEn - typically indexed by vegetation class) are due to varying conditions of light, humidity, CO2 concentration and leaf temperature. The deviations are accommodated by adjusting an effective LUE that responds to the varying conditions. We investigate the feasibility of leaf chlorophyll (Cab) to capture these variations in LUEn using remotely sensed data. To retrieve Cab from remotely sensed data we use REGFLEC, a physically based tool that translates at-sensor radiances in the green, red and NIR spectral regions from multiple satellite sensors into realistic maps of LAI and Cab. Initial results show that using Cab to estimate LUE allows for improved flux estimates over a soybean field in Iowa. The improved results indicate the necessity of a varying LUE during times of stresses induced by the environment. The results also indicate that using remotely sensed Cab to estimate LUE will allow for more accurate estimates of fluxes over space and time.
Keywords
remote sensing; vegetation; CO2 concentration; Two-Source Energy Balance; at-sensor radiances; canopy resistance; carbon assimilation; green NIR spectral region; leaf chlorophyll feasibility; leaf temperature; light-use-efficiency LUE-based model; nominal light use efficiency; nominal stand-level value; red NIR spectral region; remotely sensed data; soybean field; thermal-based TSEB model; transpiration simulations; Atmospheric modeling; Carbon; Reflectivity; Remote sensing; Soil; Temperature sensors; Vegetation mapping; Light use efficiency; carbon flux; chlorophyll; data fusion; energy fluxes; reflective shortwave;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6351974
Filename
6351974
Link To Document