Detecting leaf area and surface resistance during transition seasons

Detecting leaf area and surface resistance during transition seasons In this study we seek empirical relationships among canopy resistance to water vapor transport, the time-varying leaf area index (LAI), in situ radiative flux observations, and a satellite-based estimate of leaf state (NDVI, the normalized difference vegetation index) from a leafless deciduous forest to a covered canopy and vice versa. These relationships can be used in numerical models such as verification in global climate models. They also can be useful tools for developing remote sensing techniques. LAI was found through analysis of frequent video images of canopy evolution in spring and autumn during 1992 and 1993 at a deciduous forest in central Massachusetts. We examined the impact of leaf presence on water vapor transport during spring and autumn using an LAI time series during leaf emergence and leaf fall for the four study seasons. The canopy resistance to water vapor transport ( r c ) decreased abruptly at leaf emergence in each year but then also continued to decrease slowly during the remaining growing season, owing to slowly increasing LAI. One remarkable result is that a single linear relationship between r c . and LAI during leaf emergence can be used to estimate the minimum seasonal r c associated with the maximum foliage cover. Canopy resistance and PAR-albedo (albedo from photosynthetically active radiation (PAR) instruments) began to increase about 1 month before leaf fall with the diminishment of CO 2 gradient above the canopy as well, at which time evaporation began to be controlled as if the canopy were leafless. We present empirical linear regressions relating NDVI, r c , and PAR-albedo. The NDVI linear regressions with surface measurements indicate that tower-based measurements can represent at least a satellite pixel region. These results reinforce the notion that relationships among these parameters are scale independent from tower-based measurements spatial scale to a satellite pixel resolution (1.1 km X 1.1 km area)., at least. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agricultural and Forest Meteorology Elsevier

Detecting leaf area and surface resistance during transition seasons

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Publisher
Elsevier
Copyright
Copyright © 1997 Elsevier Ltd
ISSN
0168-1923
D.O.I.
10.1016/S0168-1923(96)02359-3
Publisher site
See Article on Publisher Site

Abstract

In this study we seek empirical relationships among canopy resistance to water vapor transport, the time-varying leaf area index (LAI), in situ radiative flux observations, and a satellite-based estimate of leaf state (NDVI, the normalized difference vegetation index) from a leafless deciduous forest to a covered canopy and vice versa. These relationships can be used in numerical models such as verification in global climate models. They also can be useful tools for developing remote sensing techniques. LAI was found through analysis of frequent video images of canopy evolution in spring and autumn during 1992 and 1993 at a deciduous forest in central Massachusetts. We examined the impact of leaf presence on water vapor transport during spring and autumn using an LAI time series during leaf emergence and leaf fall for the four study seasons. The canopy resistance to water vapor transport ( r c ) decreased abruptly at leaf emergence in each year but then also continued to decrease slowly during the remaining growing season, owing to slowly increasing LAI. One remarkable result is that a single linear relationship between r c . and LAI during leaf emergence can be used to estimate the minimum seasonal r c associated with the maximum foliage cover. Canopy resistance and PAR-albedo (albedo from photosynthetically active radiation (PAR) instruments) began to increase about 1 month before leaf fall with the diminishment of CO 2 gradient above the canopy as well, at which time evaporation began to be controlled as if the canopy were leafless. We present empirical linear regressions relating NDVI, r c , and PAR-albedo. The NDVI linear regressions with surface measurements indicate that tower-based measurements can represent at least a satellite pixel region. These results reinforce the notion that relationships among these parameters are scale independent from tower-based measurements spatial scale to a satellite pixel resolution (1.1 km X 1.1 km area)., at least.

Journal

Agricultural and Forest MeteorologyElsevier

Published: Apr 1, 1997

References

  • Maximum conductance for evaporation of global vegetation types
    Kelliher, F.M.; Leuning, R.; Raupach, M.R.; Schulze, E.D.

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