Considering Regional Connectivity and Policy Factors in the Simulation of Land Use Change in New Areas:A Case Study of Nansha New District,China

Numerous emerging development areas worldwide are receiving attention;however,current research on land use change simulation primarily concentrates on cities,urban clusters,or larger scales.Moreover,there is a limited focus on understanding the impact of regional connectivity with surrounding cities and policy factors on land use change in these new areas.In this context,the present study utilizes a cellular automata(CA)model to investigate land use changes in the case of Nansha New District in Guangzhou,China.Three scenarios are examined,emphasizing conventional locational factors,policy considerations,and the influence of regional connectivity with surrounding cities.The results reveal several key findings:(1)Between 2015 and 2021,Nansha New District experienced significant land use changes,with the most notable shifts observed in cultivated land,water area,and construction land.(2)The comprehensive scenario exhibited the highest simulation accuracy,indicating that Nansha New District,as an emerging area,is notably influenced by policy factors and regional connectivity with surrounding cities.(3)Predictions for land use changes in Nansha by 2030,based on the scenario with the highest level of simulation accuracy,suggest an increase in the proportion of cultivated and forest land areas,alongside a decrease in the proportion of construction land and water area.This study contributes valuable insights to relevant studies and policymakers alike.

Simulating multiple urban land use changes by integrating transportation accessibility and a vector-based cellular automata:a case study on city of Toronto

The accessibility provided by the transportation system plays an essential role in driving urban growth and urban functional land use changes.Conventional studies on land use simulation usually simplified the accessibility as proximities and adopted the grid-based simulation strategy,leading to the insufficiencies of characterizing spatial geometry of land parcels and simulating subtle land use changes among urban functional types.To overcome these limita-tions,an Accessibility-interacted Vector-based Cellular Automata(A-VCA)model was proposed for the better simulation of realistic land use change among different urban functional types.The accessibility at both local and zonal scales derived from actual travel time data was considered as a key driver of fine-scale urban land use changes and was integrated into the vector-based CA simulation process.The proposed A-VCA model was tested through the simulation of urban land use changes in the City of Toronto,Canada,during 2012-2016.A vector-based CA without considering the driving factor of accessibility(VCA)and a popular grid-based CA model(Future Land Use Simulation,FLUS)were also implemented for compar-isons.The simulation results reveal that the proposed A-VCA model is capable of simulating fine-scale urban land use changes with satisfactory accuracy and good morphological feature(kappa=0.907,figure of merit=0.283,and cumulative producer’s accuracy=72.83%±1.535%).The comparison also shows significant outperformance of the A-VCA model against the VCA and FLUS models,suggesting the effectiveness of the accessibility-interactive mechanism and vector-based simulation strategy.The proposed model provides new tools for a better simula-tion of fine-scale land use changes and can be used in assisting the formulation of urban and transportation planning.