Optimizing Land Use Allocation Based on Ant Colony Algorithm Under Ecological Security Constraints

Optimizing land use allocation in terms of ecological security has practical significance for coordinating ecological protection and land exploitation and utilization. However, previous studies have mainly focused on ecological security-oriented land use simulation rather than optimal allocation, failing to consider whether the resulting land use scheme satisfies stakeholders’ objectives. In this study, we developed a multi-objective land use optimization allocation framework that incorporates ecological security by integrating the minimum cumulative resistance (MCR) model and an ant colony optimization (ACO) algorithm and applied it to optimal land allocation scheme creation in the Pearl River Delta (PRD) in China. The results showed the following: the proposed framework is proven to be effective for generating optimal land use patterns that consider both the needs of economic development for land use and ecological land protection, thus having potential in providing technical support for territorial spatial planning. Compared with the 2020 land use of PRD, the optimized allocation scheme for 2035 improved the total objective value, land suitability, land aggregation degree, and conversion benefit on the basis of managing trade-offs between these objectives and provided a better land use structure guarantee for regional sustainable development. Furthermore, the resulting land allocation scheme could reduce the fragmentation degree and diversity of the landscape, increase land aggregation degree, and more reasonably allocate the distribution of various land types. This study provides a reference for territorial spatial planning given an ecological security premise.