Coupling Earth observation and eddy covariance data in light-use efficiency based model for estimation of forest productivity
- Resource Type
- article
- Authors
- Ritika Srinet; Subrata Nandy; Taibanganba Watham; Hitendra Padalia; N. R. Patel
- Source
- Geocarto International, Vol 37, Iss 25, Pp 7716-7732 (2022)
- Subject
- gross primary productivity
plant functional types
remote sensing
photosynthetically active radiation
google earth engine
Physical geography
GB3-5030
- Language
- English
- ISSN
- 1010-6049
1752-0762
10106049
The light use efficiency (LUE) approach is a well-established method for estimating gross primary productivity (GPP) over large areas using Earth observation data. The present study aims to determine maximum light use efficiency (LUEmax) values specific to the northwest Himalayan foothills of India. It also aims to estimate the spatio-temporal variability of GPP from 2001 to 2020 using remote sensing data in combination with eddy covariance data in the LUE-based model. The model was parameterized using different sets of default and calculated parameters. The study showed that the use of PFT-specific LUEmax and temperatures increased the accuracy of the model predictions. On validation, the LUE-based model predicted GPP showed R2 = 0.82 for moist deciduous and R2 = 0.83 for dry deciduous PFTs. The study revealed that with rigorous model parameterization, RS data can be used in an LUE-based model to achieve accurate spatio-temporal estimates of GPP.