To address the complex ecological disturbances along transmission lines and that the restoration areas are not clearly identified, a regional identification and management system for multiple factors has been put forward in this study. A graph-structured input system with the five types of categories has been built: topography, hydrology, soil, land use and human activity. Fuzzy C-means and spectral clustering are combined for partition modelling, and a strategy template response matching mechanism is also employed. A rolling optimisation module is added to support block-level management of the deployment pathway. A typical ecological pattern in Jiangxi Province is selected as the experimental area. Approximately 97.4 kilometres of a strip-shaped simulated corridor is taken out independently as the modelling area in the regional background data framework. Thus, 236 grid units and 117 disturbance samples were created for the comparative experiments. According to the above experimental results, the new way of zoning recognition outperforms that of the previous methods in terms of zoning recognition accuracy (94.6%), policy hit rate (91.4%), and boundary coherence (85.3%); it is also highly reliable and feasible for use in engineering applications. This paper puts forward a multi-factor graph model to improve the accuracy of ecological restoration zone identification for transmission lines and achieve closed-loop optimisation of disturbance identification and strategy scheduling.
