[Objective] Under the dual-carbon goals and sustainable development framework, the development of regional carbon eco-compensation mechanisms plays a pivotal role in reconciling the conflict between economic growth and ecological preservation during land development. [Method] Focusing on Anhui Province, this study establishes an integrated “spatiotemporal differentiation-network connectivity-compensation zoning” framework. Through combined application of network analysis, carbon eco-compensation modeling, entropy weight-TOPSIS method, and K-means algorithm, a differentiated carbon compensation scheme based on Sustainable Development Goals (SDGs) was established. [Result] 1) Significant spatial heterogeneity in net land-use carbon emissions, exhibiting distinct north-south and east-west gradients with higher emissions concentrated in northern and eastern regions during the study period. 2) Emergence of a hierarchical carbon network structure with Hefei as the core node and Wuhu, Ma’anshan, and Huainan as intermediary hubs, demonstrating enhanced network connectivity and core-periphery configuration over time. 3) The spatial difference of carbon compensation value is obvious, the total carbon payment and carbon compensation amount are 109.89×108 yuan and 25.23×108 yuan respectively, and 7 payment zones and 10 compensation zones are identified. 4) Combined with the sustainable development of the city, 7 types of carbon integrated ecological compensation management zones are formed, and the differentiated carbon ecological compensation suggestions of "gradient compensation - collaborative governance" are proposed for each type of area. [Conclusion] The analytical framework and policy recommendations offer critical references for optimizing cross-regional ecological compensation mechanisms and advancing low-carbon spatial governance paradigms. Particularly noteworthy is the novel integration of complex network theory with multidimensional zoning methodology, providing a replicable model for regional carbon management in developing economies.