The Study Of Scale Sensitivity Quantitative Method In Land Use Change Cellular Automata Modeling

The spatial pattern of land use has undergone tremendous changes in human activities,which results in a lot of natural and social environmental problems.Therefore,accurate grasping the land use information and the dynamic situation,simulating land use change and forecasting of the spatial evolution of information,which provide a basis reference for urban decision-makers to rational use and development of land resources.The cellular automata(CA)model has become a powerful tool,which could simulate the land use change with their powerful spatial and temporal dynamic simulation capabilities and local interactions,In addition,with the rapid development of earth observation technology,satellite remote sensing image can provide a rich data source,which greatly promotes the research of urban land use change simulation using CA model.However,due to the different scales of the model influence factors,scale sensitivity exist in the process of land use change simulation by CA model in practical applications,which will affect the final simulation accuracy.These factors mainly include cell size,neighborhood size and neighborhood type.Different scales of these factors easily result in different comprehensions to the procedure of land use change simulation.Thus,it is crucial to effectively describe and analyze these sensitivities,as well as measure them for improving simulation accuracy and enhancing the reliability of the results.In this paper,CA-Markov model is taken as an example.First,the accuracy evaluation index is selected,and the simulation accuracy and error distribution are considered from the numerical and spatial distributions.A scale evaluation method of coupled kappa coefficient and contag index is constructed,and keep a record of CA-Markov simulation process.Then,by introducing the response surface method as a measure of the quantitative sensitivity of the model,the scale sensitivity of the input factors is quantitatively studied,and the interaction between multiple factors is analyzed.Finally,based on the optimal combination of scales,the SLEUTH model is introduced to compare the difference between urban expansion model and spatial pattern of land use change simulation with CA-Markov.The main results of this paper are as follows:(1)Selecting the accuracy evaluation index(including Kappa coefficient and Contag index),and constructing the coupling scale sensitivity evaluation model.These can measure the combined effect of numerical error and spatial distribution error on the simulation results.In addition,Supported by the indicators of the evaluation results,the coupled contag index and kappa coefficient is better than the kappa coefficient alone.(2)The response surface method is used to quantify the scale sensitivity of CA-Markov model.The interaction between contours and response surfaces can fully identify the interaction between cell size,neighborhood size and neighborhood shape.And the relationship between the influencing factors and the simulation accuracy is given by establishing the multiple regression equation.Then optimal scale combination was acquired,which included that cell size is at 90 m,the neighborhood size is 3 × 3 cells,and the neighborhood shape is Von.Neumann.(3)Based on the comparison of CA-Markov and SLEUTH model,it is found that CA-Markov has a high urban density and and cluster distribution,and the SLEUTH model has a low density.In addition,the CA-Markov model is more accuracy than the SLEUTH model and is closer to the real situation.In this paper,CA-Markov model is taken as an example to study the scale sensitivity quantitative method in land use change cellular automata modeling.The experimental results show that the evaluation index and quantitative method are reasonable,and the CA-Markov model is proved to be a classic position in simulating land use change.This plays an active role in effectively using scientific models and evaluation methods to improve simulation accuracy.