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