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• The network structure characteristics of land-use carbon emissions (LUCE) are explored. • The problems of synergistic CO 2 reduction in Jiangxi province were identified. • The LUCE network structure in study areas becomes increasingly intricate and stable. • The LUCE spatial correlation network exhibited pronounced spatial spillover effects. • The study combines new relevant indicators to conduct carbon balance zoning. Exploring the spatial network structure of land-use carbon emissions (LUCE) and the carbon balance in developing regions is pivotal for climate change mitigation in these areas. Using socio-economic and land-use data from 2000 to 2020, this study focused on Jiangxi Province as a representative case to elucidate the spatial network structure of LUCE and conduct carbon balance zoning. The primary findings were as follows: (1) The LUCE distribution in Jiangxi Province demonstrated a spatial pattern with high values in the northwest and low values in the southeast. An increasing trend was observed in the total amount of LUCE. Furthermore, there were evident regional differences in the Ecological Support Coefficient (ESC), indicating a weakening regional carbon sink capacity. (2) The spatial network structure of LUCE was intricate but stable. Although the gravitational interactions of LUCE between cities have intensified, overall network connectivity remained moderately correlated, indicating a prominent regional development imbalance. (3) There was a pronounced "core-periphery" structure in the LUCE spatial correlation network. Northern Jiangxi was the "core" of the network, taking an "initiator" role, whereas most cities in southern Jiangxi played a "passive" role, and resided at the "periphery" of the network. The inter-regional LUCE network exhibited pronounced spatial spillover, with inter-block correlations surpassing those within blocks. (4) By leveraging empirical data and spatial metrics, we categorized Jiangxi Province into five distinct carbon balance zoning types and subsequently proposed land-use optimization strategies. From the perspective of social network analysis (SNA), this study offers methodological insights into low-carbon development and synergistic emission reduction in developing regions. [ABSTRACT FROM AUTHOR]