Simulation and Optimization of Urban–Rural Settlement Development from the Perspective of Production–Life–Ecology Space: A Case Study for Aksu City

Abstract

To explore the future development state of urban and rural settlements, we combined random forest algorithm (RFA) and cellular automata (CA) to simulate high precision in urban and rural settlements in Aksu city. The settlement distribution was predicted for the next 10 years, and suggestions for urban and rural settlements were proposed based on a “production–life–ecology” space. The results show the following: Transportation factors and administrative location have an important influence on the development of settlements, and infrastructure has a greater impact on the development of settlements. The overall accuracy of the 2019 settlement distribution obtained through the RFA–CA model simulation is 93.8%, with a G-mean coefficient of 0.815. The simulation accuracy is better and more suitable for the simulation and prediction of settlement expansion than the logistic-CA model. The forecasted settlement expansion in 2029 for Aksu city is 58.36 km2 of settlement expansion compared to the 2019 settlement distribution, with an overall growth trend for sparse north-south and dense central areas. This study analyzed the causes of settlement expansion in 19 regions of Aksu city, explored the main function of “production–life–ecology” space in different areas, and proposed layout optimizations from the perspective of production, life, and ecology. The results of this study can provide a reference for the spatial planning and rural revitalization strategy of Aksu city.

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