Optimizing the spatial pattern of "production-living-ecological" spaces is conducive to achieving regional sustainable and high-quality development. This study introduced a methodology for optimizing the spatial pattern of "production-living-ecological" spaces, called DTTD-MCR-PLUS. Considering the spatial heterogeneity of land expansion costs, the Minimum Cumulative Resistance (MCR) method and mutation detection were applied to conduct quantity optimization in "production-living-ecological" spaces, and a patch-generating land use simulation (PLUS) model was used to reflect its spatial distribution under three different scenarios containing food security, ecological priority and production priority. Furtherly, the dynamic traffic time data (DTTD) was innovatively introduced to portray living and ecological space expansion cost. The research found that:(1) After the ecological function optimization zoning, the core protection area of Changsha's ecological space was 4111.41 km², the edge protection area of ecological space was 2285.29 km², the key area of production space was 2144.79 km², and the area of production space was 1928.59 km². In addition, the area of the concentrated living space expansion area was 2570.99 km². (2) The multi-scenario results simulated by the coupled DTTD-MCR-PLUS model revealed that:under the living priority scenario, the living space area increased by 43.57%, which was mainly distributed in the southern part of the urban area, the western part of Changsha County, and the eastern part of Yuhua District. Under the ecological priority scenario, the land transition-out of ecological space is the lowest compared with other scenarios, which was 3.11% lower than that of living priority scenario. Under the food security scenario, the proportion of encroachment of production space into ecological space was accelerated, with an increase of up to 58.79%. (3) The results of coordinating the basic farmland, ecological protection red line, nature protected area, and the optimized Changsha's "production-living-ecological" spaces in 2030 showed that, the proportions of production space, living space and ecological space were 37.63%, 7.67%, and 54.70%, respectively.