Analysis of spatial-temporal variation and multiscenario simulation of land use in Chongqing based on MOP-MCCA model

Land resources are the basic elements to maintain the survival and development of human society. It is of great significance to deeply explore the evolution mechanism and future trend of its utilization pattern. Taking the typical mountainous city of Chongqing as the study subject, this research comprehensively employs the Land Use Transition Matrix, Multi-Objective Optimization (MOP) model, and Hybrid Cellular Automata (MCCA) model based on 2000–2020 remote sensing data of land use, socioeconomic data, and natural geographic data. It systematically analyzes the spatiotemporal characteristics of land use change in Chongqing and conducts multi-scenario simulations. Results indicate: (1) Human activities significantly influence land use changes in Chongqing, primarily manifested in mutual conversions between farmland, construction land, and other land categories. The Grain-for-Green Program drives farmland conversion to forest and grassland, while urbanization processes lead to multiple land categories transforming into construction land, resulting in a significant increase in construction land area. (2) The multi-objective optimization (MOP) model effectively quantifies and balances conflicts among multiple objectives—including socioeconomic development, ecological conservation, and food security—providing critical decision-making support for optimizing Chongqing's future land use structure. (3) The MOP-MCCA coupled model developed in this study demonstrated high accuracy in multi-scenario land use simulations, with an overall accuracy (OA) of 0.895, a Kappa coefficient of 0.809, and an mcFoM value of 0.201. This indicates the model's applicability for land use simulation research in complex mountainous environments.