Abstract
Sustainable development is a commonly pursued goal worldwide, and assessing urban sustainability has gradually become central to formulating urban development policies and planning. The sustainable use of land resources is the foundation and prerequisite for sustainable urban development. To dynamically assess and predict urban sustainability, and to optimize land use/land cover (LULC) structure and distribution patterns, we propose a novel framework that combines the ecological footprint model, BPNN, multi-objective genetic algorithm (MOGA), and patch-generating land use simulation (PLUS) model, and apply it to Bortala, China. The results showed that, from 2000 to 2020, the EF of Bortala initially grew and then stabilized, while the ecological carrying capacity (EC) was basically stable. In the study area, the LULC structure and distribution patterns under the LULC optimization scenario had a higher EC and a lower ecological deficit compared to the natural development scenario. The results of this study provide new insight into the allocation of land resources, the improvement of EC, and the formulation of socio-economic development policies.
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