Estimating the relative abundance of C3 and C4 grasses in the Great Plains from multi-temporal MTCI data: issues of compositing period and spatial generalizability
Estimating the relative abundance of C3 and C4 grasses in the Great Plains from multi-temporal MTCI data: issues of compositing period and spatial generalizability
Accommodating for the differences between grasses following the C3 and C4 photosynthetic pathways in environmental research often requires information on their spatial distribution and relative abundance. Multi-temporal remote sensing
may indicate the latter because these grasses have asynchronous phenologies.
The relationship between remotely sensed variables and grassland composition, defined by C3(%), was explored with attention focused on two key issues associated
with studies of large areas from multi-temporal datasets: the compositing period used and spatial generalizability of a selected relationship. MERIS Terrestrial Chlorophyll Index (MTCI) composites of the Great Plains were generated using
compositing periods of 5, 7, 10 and 14 days. The results of a regression analysis indicated that a relationship between MTCI data and grassland composition may be formulated for the State of South Dakota with R2 ,0.6. The strength of the relationship was, generally, strongest for short compositing periods. The transferability of the relationship to other regions was, however, limited by its significant non-stationarity indicating a challenge for large area studies
351-362
Foody, Giles M.
62843823-1717-4a6e-9dd6-72539e7bf44e
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
March 2010
Foody, Giles M.
62843823-1717-4a6e-9dd6-72539e7bf44e
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Foody, Giles M. and Dash, Jadunandan
(2010)
Estimating the relative abundance of C3 and C4 grasses in the Great Plains from multi-temporal MTCI data: issues of compositing period and spatial generalizability.
International Journal of Remote Sensing, 31 (2), .
(doi:10.1080/01431160902887339).
Abstract
Accommodating for the differences between grasses following the C3 and C4 photosynthetic pathways in environmental research often requires information on their spatial distribution and relative abundance. Multi-temporal remote sensing
may indicate the latter because these grasses have asynchronous phenologies.
The relationship between remotely sensed variables and grassland composition, defined by C3(%), was explored with attention focused on two key issues associated
with studies of large areas from multi-temporal datasets: the compositing period used and spatial generalizability of a selected relationship. MERIS Terrestrial Chlorophyll Index (MTCI) composites of the Great Plains were generated using
compositing periods of 5, 7, 10 and 14 days. The results of a regression analysis indicated that a relationship between MTCI data and grassland composition may be formulated for the State of South Dakota with R2 ,0.6. The strength of the relationship was, generally, strongest for short compositing periods. The transferability of the relationship to other regions was, however, limited by its significant non-stationarity indicating a challenge for large area studies
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Published date: March 2010
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Local EPrints ID: 72171
URI: http://eprints.soton.ac.uk/id/eprint/72171
ISSN: 0143-1161
PURE UUID: 019467fb-2128-42a3-b9de-ca3d88a867e9
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Date deposited: 27 Jan 2010
Last modified: 14 Mar 2024 02:48
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Author:
Giles M. Foody
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