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24 October 2018 Canopy conductance index for GPP estimation from it's capacity
Kanako Muramatsu
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Proceedings Volume 10777, Land Surface and Cryosphere Remote Sensing IV; 107770M (2018) https://doi.org/10.1117/12.2324247
Event: SPIE Asia-Pacific Remote Sensing, 2018, Honolulu, Hawaii, United States
Abstract
The characteristics of this GPP estimation method correspond to the photosynthesis process. The photosynthetic rate varies from it's capacity by weather conditions, where depression thereof is controlled by stomatal opening and closing. In this study, we used flux data from a dry area and Moderate Resolution Imaging Spectrometer (MODIS) surface temperature products to define a canopy conductance index. First, we studied the contribution ratios of elements of canopy conductance using the big-leaf model with diurnal change flux data averaged over 8 days. Next, the correlations of meteorological and flux elements with surface temperature data from MODIS were studied. The largest contributor to the denominator of canopy conductance was found to be vapor pressure deficit (VPD), and that of the numerator was evapotranspiration. During the period around noon, evapotranspiration did not change dramatically and the canopy conductance index was estimated as the slope of 1/VPD, which changes over time. In the dry area, the surface temperatures around 11 a.m. and 1 p.m. were strongly correlated with VPD at 11 a.m. and 1 p.m., respectively. For dry areas, therefore, the slope of 1/VPD can be estimated using surface temperature data from satellite sensors.
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Kanako Muramatsu "Canopy conductance index for GPP estimation from it's capacity", Proc. SPIE 10777, Land Surface and Cryosphere Remote Sensing IV, 107770M (24 October 2018); https://doi.org/10.1117/12.2324247
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KEYWORDS
Satellites
MODIS
Data modeling
Earth observing sensors
Photosynthesis
Vegetation
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