Abstract
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.
Acknowledgements
The present study was carried out as a part of Soil-Vegetation-Atmosphere-Flux (SVAF) of National Carbon Project (NCP) supported by ISRO-Geosphere-Biosphere Programme. The authors sincerely thank the Director, Indian Institute of Remote Sensing, ISRO, Dehradun, for the encouragement and support for this study. Authors are thankful to the MODIS Science team for the Science Algorithms, the Processing Team for producing MODIS data, and the GES DAAC MODIS Data Support Team for making MODIS data available to the user community. The authors would also like to thank the European Centre for Medium-Range Weather Forecasts (ECMWF) and Copernicus Climate Change Service for providing ERA-5 data. Thanks are also due to the anonymous reviewers for their valuable suggestions, which helped us to improve the manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.