# Multiscenario Simulation and Prediction of Land Use in Huaibei City Based on CLUE-S and PLUS Models
## 1 Introduction  
As an important component and major cause of global environmental change, land use/land cover change (LUCC) is a manifestation of human-earth system interaction, which is driven by natural and anthropogenic factors but also directly affects the processes of material exchange and energy cycling in the hydrosphere, pedosphere, atmosphere, and biosphere [1; 2; 3]. While global environmental changes have been studied intensively, problems caused by LUCC have been discussed and studied extensively, such as loss of farmland, water pollution, and biodiversity reduction. Therefore, exploring both historical and future scenarios of ULCs is crucial in making sensible proposals for sustainable development [4].  
With the advancement of geographic information systems (GIS) and remote sensing (RS), LUC modeling has become one of the main methods to research LUC. Models are important tools for exploring LU driving factors, supporting urban planning and policy making, and assessing the ecological impact of LU [5]. Scholars now mainly use integrated models to make up for the inadequacy of separate models. [PERSON] et al., coupled the conversion of land use and its effects (CLUE-S) model with the Markov, gray prediction, and linear regression methods, respectively, to compare the three simulation results and set two future scenarios within the Qinhuai River basin [6]. [PERSON] et al., coupled the system dynamics (SD) model, patch-generating land use simulation (PLUS) model, and integratedvaluation of ecosystem services and tradeoffs (InVSET) model to simulate the LU and carbon storage changes in Bortala based on the CMIP6 published climate change scenarios [7]. [PERSON] et al., predicted LUC for agricultural development in primary planted areas of the Cerrado and Atlantic woodland intersections in Brazil using CA-Markov [8]. Apart from the above models, the future land use simulation (FLUS) model [9] and agent-based model (ABM) are also common [10]. Spatial models are particularly important among the hybrid models, with different spatial models exhibiting different simulation results and differences in the suitable regions. The FLUS model allows for nondominant land class conversion and can simulate leapfrog development scenarios. However, it is difficult to clearly reflect spatial differences in land use changes in different locations. The ABM model is suitable for the dynamic simulation of policy-driven urban expansion and land use changes, but it is difficult to represent the spatial behavior of the subject [4]. The CLUE-S model is applicable to LUC research on a small scale and can simulate multiple land use changes simultaneously. It has been widely used in previous research with high simulation accuracy [11; 12]. The PLUS model is improved on the basis of the FLUS model, which explains the influencing factors of LUCs well, and can better model the LU patch-level changes with high simulation accuracy [13; 14]. Therefore, we compared the CLUE-S and PLUS models and chose the model that was more applicable to the region.  
Huaibei City is one of the top ten coal bases in China. For many years, the mining of coal resources has made the city pay a heavy price in terms of land sinkage, near resource depletion, and ecological degradation [15]. So, this study analyzed the LUC in Huaibei City between 1985 and 2020. The CLUE-S model and PLUS model were selected to simulate the spatial landscape of LU in 2020. Simulation results of the two models are compared to explore possible future scenarios and support decision making for the future.