Multi-scale Correlation Analysis on Land-Use Change and Economic Factors in a Typical Region of Wavelet Transforming

The analysis of multi-scale land-use change and the driving force factors behind it has become an important direction for research In this study,a wavelet analysis tool was applied to analyze the multi-scale correlation between land-use change and economic factors based on characteristic scale analysis.The results showed that,in the study area,the scale of 64m was regarded as the characteristic scale and optimal to identify land-use heterogeneity.Wavelet variance revealed local information but failed to describe the general spatial pattern of land-use at a finer scale,and shapely raised for combination of information along with the upscaling.The results indicated that correlation between land-use change and economic factors was scale-dependent: the correlation coefficient values were smaller at a finer scale and reached the extreme at the characteristic scale.However,at a coarser scale,the correlation coefficient values of most economic factors became flat.This analysis suggests that economic factors effecting land-use change are macro constraints,and at the same time,shows the effectiveness of characteristic scale analysis.The coefficients among different factors are also different,under high-frequency wavelet coefficients there was strong positive correlation between population and land-use change at each scale,but a weak negative correlation in Per Capita income of rural households,suggesting that population was the most influential factor in land-use change.This study shows that wavelet analysis is a powerful tool for multi-scale correlation analysis,and can effectively reveal the multi-scale spatial patterns in land-use change.