Many ecological systems follow a seasonal cycle affecting primary production,
carbon flux, and vegetative gas emissions. The seasonal variation of ecological
systems are both affected by and have effects upon climatic factors. A quantitative
estimate of the seasonal variation of vegetation is required to characterize ecological
systems and their interaction with climate. Monitoring the spaliotemporal
variation of foliar biomass density (FBD) over one year will provide a quantitative
estimate of the annual cycle and regional variation of photosynthetic activity. FBD
is a quantitative measure of leafy material per unit of area produ\:ed by photosynthetically
active vegetation. This seasonal variation in FBD is an important parameter
for global and other large scale investigations of ecological, hydrological, and
biogeochemical systems which require data and expertise from a variety of sources
and disciplines. Therefore, FBD is potentially of great utility for ecologists,
hydrologists, climatologists, and atmospheric scientists.
Recent regional scale investigations of ecological systems concluded that the
repetitive coverage and synoptic view of remotely sensed measurements provide
data to monitor the seasonal variation of biomass. A method to estimate the seasonal
variation of FBD at global scales has not been developed. The objective of
this research is to develop a methodology that could be used to estimate the
seasonal variation of FBD for the entire terrestrial biosphere. By coupling global
satellite data, measured field data, and a vegetation classification, a model was
developed to estimate the global spatiotemporal variation of FBD.
Comparisons between literature estimates of FBD and estimated FBD from
this model were made as a means of validation. A more specific comparison was
conducted between grasslands based on work conducted in the Senegalese Sahel
region in Africa. Finally, a sensitivity analysis was performed to characterize the
potential propagation of error associated with the literature FBD estimates used to
drive this model. / Graduation date: 1992
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/37239 |
| Date | 24 May 1991 |
| Creators | Pross, Derek D. |
| Contributors | Kiimerling, A. Jon |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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