Simulation of land use evolution and spatial optimization in Tai'an City coupled with the GeoSOS model and ant colony algorithm

Territorial spatial planning plays a pivotal role in balancing ecological conservation and economic development, with its core lying in accurately simulating land-use changes and optimizing spatial layouts. This study, using Tai'an City as a case, coupled the GeoSOS model with the ant colony optimization(ACO)algorithm to simulate land-use changes and spatial optimization patterns for 2035 under three scenarios: inertial expansion of construction land, restriction of construction land, and dual restrictions on construction land scale and spatial morphology. Indicators such as landscape division index, splitting index, and effective mesh size were employed to quantitatively evaluate the fragmentation and spatial optimization performance of land-use patterns under each scenario. The results demonstrate that the dual restriction scenario effectively controls the expansion scale of construction land, resulting in more compact spatial patterns, improved land-use and ecological conservation efficiency. The findings provide a scientific basis for optimizing the territorial spatial structure of Tai'an City and offer technical support for similar cities in developing eco-friendly and resource-efficient territorial spatial planning strategies.