Gross primary productivity (GPP) is the largest
and most variable component of the global terrestrial carbon
cycle. Repeatable and accurate monitoring of terrestrial
GPP is therefore critical for quantifying dynamics in
regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is
widely used to monitor and...
Gross primary productivity (GPP) is the largest
and most variable component of the global terrestrial carbon
cycle. Repeatable and accurate monitoring of terrestrial
GPP is therefore critical for quantifying dynamics in
regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is
widely used to monitor and...
Accurate and reliable estimates of gross primary productivity (GPP) are required for monitoring the global carbon cycle at different spatial and temporal scales. Because GPP displays high spatial and temporal variation, remote sensing plays a major role in producing gridded estimates of GPP across spatiotemporal scales. In this context, understanding...
Accurate and reliable estimates of gross primary productivity (GPP) are required for monitoring the global carbon cycle at different spatial and temporal scales. Because GPP displays high spatial and temporal variation, remote sensing plays a major role in producing gridded estimates of GPP across spatiotemporal scales. In this context, understanding...
Accurate and reliable estimates of gross primary productivity (GPP) are required for monitoring the global carbon cycle at different spatial and temporal scales. Because GPP displays high spatial and temporal variation, remote sensing plays a major role in producing gridded estimates of GPP across spatiotemporal scales. In this context, understanding...
Gross primary productivity (GPP) is the largest
and most variable component of the global terrestrial carbon
cycle. Repeatable and accurate monitoring of terrestrial
GPP is therefore critical for quantifying dynamics in
regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is
widely used to monitor and...
Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (V[subscript cm]), and quantum yield (alpha) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index...