Validation of Gross Primary Production Estimated by Remote Sensing for the Ecosystems of Doñana National Park through Improvements in Light Use Efficiency Estimation

A novel approach to estimating gross primary production (GPP) in Doñana National Park, Spain, demonstrates that the inclusion of the Sentinel-2 Land Surface Water Index (LSWI) significantly improves model accuracy compared to traditional light use efficiency (LUE) models. The study, validated with eddy covariance data from two distinct ecosystems—xeric shrubs and seasonal marshes—reveals that water status has a greater influence on GPP than meteorological variables in this water-scarce region. This finding underscores the potential of integrating remote sensing data to enhance carbon assimilation monitoring in heterogeneous landscapes, offering critical insights for global change research.

Gómez-Giráldez, P. J., Cristóbal, J., Nieto, H., García-Díaz, D., & Díaz-Delgado, R. (2024). Validation of Gross Primary Production Estimated by Remote Sensing for the Ecosystems of Doñana National Park through Improvements in Light Use Efficiency Estimation. Remote Sensing, 16(12), 2170. https://doi.org/10.3390/rs16122170