Spatial and temporal distribution of NEE in Babao River Basin based on multisource remote sensing data

Net Ecosystem Exchange (NEE) is a crucial metric for assessing carbon cycling, and its accurate quantification is vital for understanding carbon cycle processes. This study employs a previously developed multimodal feature fusion model (MMCA-RF), integrating multi-source remote sensing data, topographic features, and meteorological elements to achieve high-precision estimation of NEE in the Babao River Basin on the northeastern margin of the Tibetan Plateau. Results revealed that the spatial distribution of basin NEE exhibited altitudinal differentiation: low-elevation river valleys function as strong carbon sinks, whereas high-elevation zones predominantly act as weak sinks or carbon sources; Seasonal dynamics exhibited a typical single-peak feature, with a carbon sink peak of -42 gCm⁻²month⁻¹ in July. Grasslands showed the strongest seasonal fluctuations in NEE (CV=0.61), shrublands peaked later in August, while open woodlands maintained the most stable carbon uptake. This study offers critical insights into the synergistic regulatory mechanisms of altitude and vegetation on the carbon cycle in alpine regions.