The Use of an Optimized Grey Multi-Objective Programming-PLUS Model for Multi-Scenario Simulation of Land Use in the Weigan–Kuche River Oasis, China

The oasis serves as the primary supply of cultivable land, along with the hub for human production and habitation in Xinjiang. Accordingly, predicting the land use of these areas based on various goals is an effective instrument for encouraging the sensible distribution of resource space. The study investigated the creation of a land use-allocation optimization model based on the various objectives of ecological protection, food security, and urban growth using the Weigan–Kuche River oasis as an example. The GMOP-PLUS model’s restriction conversion area was adjusted to include the findings of the land suitability evaluation. Additionally, it optimized and simulated the spatial arrangement and quantitative structure of land usage in the Weigan–Kuche River oasis in 2035. The results indicate the following: (1) the model’s overall accuracy is 89.36%, and its Kappa coefficient is 0.872, more than 0.8. Thus, the model can be considered for adoption in the future when predicting changes in land use in the districts and counties of the Weigan–Kuche River oasis; (2) based on the results of the land suitability evaluation, the percentage of areas that are most suited for agricultural development, urban development, and ecological protection is 39.32%, 24.21%, and 14.06%, respectively; and (3) the three scenarios satisfy the various demands for growth within the oasis, and the land use structure of the oasis varies considerably in response to the various development objectives, with the construction and cultivated land undergoing the most substantial modifications. The multi-scenario simulation of land usage in the oasis can provide essential support and a range of perspectives for future land spatial planning and socioeconomic development decision-making in the Weigan–Kuche River oasis. This is essential for both the efficient use of land resources and sustainable development.