Integrating biophysical and biochemical indicators for assessing ecosystem functional capacity using multi-source remote sensing

Understanding seasonal variations in vegetation’s biophysical and biochemical features is crucial for assessing ecosystem response to climate change and carbon dynamics. This study used multiple remote sensing data sources (Landsat 8, MODIS, and ERA5-Land) to assess vegetation characteristics, Gross Primary Productivity (GPP), and ecosystem functional capacity (F) in Skåne County, Sweden between winter and summer 2024. Key variables, including NDVI, EVI, LAI, LST, LSWI, fPAR, and chlorophyll metrics, were calculated, and GPP was approximated using a Light Use Efficiency (LUE) model restricted by environmental stress factors. The results showed significant seasonal fluctuation, with LAI ranging from 0.13 to 1.80, with values greater than 1.0 indicating healthy vegetation. The shrubland saw an increase in GPP from 2.98 to 3.39 g C m−2 day−1 from winter to summer. Strong correlations (R2 = 0.92) and nonlinear connections between paired indices indicate threshold-driven ecological responses. During the summer, functional capacity rose, indicating improved vegetative resilience and carbon assimilation. These findings argue for better monitoring of ecosystem health and carbon sink capacity in the context of climate change.