DocumentCode :
2127918
Title :
Coupling a Canopy Reflectance Model with a Global Vegetation Model
Author :
Quaife, Tristan ; Lewis, Philip ; Disney, Mathias ; Lomas, Mark ; Woodward, Ian ; Picard, Ghislain
Author_Institution :
Dept. of Geogr., Univ. Coll. London
Volume :
1
fYear :
2004
fDate :
20-24 Sept. 2004
Lastpage :
11
Abstract :
Assimilation of Earth Observation (EO) data into Dynamic Vegetation Models (DVMs) can either be via derived products (e.g., LAI or fAPAR) or through radiances. Successful assimilation generally requires that the distribution of errors in an observed variable is well known. Radiance measurements conform to this requirement more strongly than derived products which have undergone more complex processing and whose relation to the true value of the estimated variable is poorly understood. To enable radiances to be assimilated a DVM must be able to predict canopy leaving radiation. To do this it is necessary to couple it with a Canopy Reflectance Model (CRM). As DVMs require some concept of intercepted radiation to drive photosynthesis and ultimately plant growth, there is a common framework between DVMs and CRMs which may be exploited for this purpose. This paper describes the mechanisms by which a simple radiative transfer CRM can be coupled with a DVM and discusses the disparities in the assumptions made by each concerning photon-vegetation interactions. Results of forward modelled canopy reflectances are presented and compared with EO estimates of reflectance
Keywords :
atmospheric boundary layer; atmospheric ionisation; atmospheric radiation; photosynthesis; CRM-GVM coupling; Canopy Reflectance Model; DVM; Dynamic Vegetation Model; EO data assimilation; Earth Observation data; Global Vegetation Model; LAI derived product; Leaf Area Index; atmospheric radiance measurement; canopy leaving radiation prediction; error distribution; fAPAR derived product; fraction of Absorbed Photosynthetically Active Radiation; photon-vegetation interaction; photosynthesis; plant growth; radiative transfer model; Animals; Atmospheric modeling; Data assimilation; Earth; Educational institutions; Electromagnetic coupling; Geography; Mathematics; Reflectivity; Vegetation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-8742-2
Type :
conf
DOI :
10.1109/IGARSS.2004.1368931
Filename :
1368931
Link To Document :
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