Observations-based GPP estimates
Abstract
We have developed global estimates of gross primary production based on a relatively simple satellite observations-based approach using reflectance data from the MODIS instruments in the form of vegetation indices that provide information about photosynthetic capacity at both high temporal and spatial resolution and combined with information from chlorophyll solar-induced fluorescence from the Global Ozone Monitoring Experiment-2 instrument that is noisier and available only at lower temporal and spatial scales. We compare our gross primary production estimates with those from eddy covariance flux towers and show that they are competitive with more complicated extrapolated machine learning gross primary production products. Our results provide insight into the amount of variance in gross primary production that can be explained with satellite observations data and also show how processing of the satellite reflectance data is key to using it for accurate GPP estimates.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.B51H1928J
- Keywords:
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- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCES;
- 0428 Carbon cycling;
- BIOGEOSCIENCES;
- 0439 Ecosystems;
- structure and dynamics;
- BIOGEOSCIENCES;
- 0480 Remote sensing;
- BIOGEOSCIENCES