基于增强回归树和Logistic回归的城市扩展驱动力分析

研究城市扩展驱动力对于准确判断城市发展规律,剖析演化过程和预测城市未来扩展趋势具有重要意义,同时也能为制定合理的调控政策提供指导。以沈阳市1997—2010年城市建成区变化作为因变量,选取三大类10种驱动因子,利用增强回归树(BRT)和Logistic回归两种方法分析影响城市扩展的主要驱动力。结果表明:(1)BRT分析得到影响沈阳城市扩展的驱动因子从大到小依次是:距1997年城区距离、距河流距离、数字高程模型DEM、距高速公路和铁路距离、土地利用类型、开发区规划、GDP、人口密度、坡向和坡度;(2)Logistic回归分析得到影响沈阳城市扩展的前8位驱动因子依次是:开发区、距1997年城区距离、DEM、距高速公路和铁路距离、人口密度、距河流距离、农村居民点和坡度;(3)距1997年城区距离、DEM、距高速公路和铁路距离是影响沈阳城市扩展的主要驱动力,均位于主要因子的前四位;(4)总体来说,沈阳城市扩展受邻域因子影响最大,而自然因子的影响相对较小,社会经济因子则只有开发区和农村居民点对城市扩展影响较大。

Driving forces analysis of urban expansion based on boosted regression trees and Logistic regression

The rapid relentless urban area expansion has led to a series of problems in China. Many researches focused on this issue in recent years. Driving forces are the core topic in urban expansion,as well as the basic component of modeling and predicting. It is very useful and meaningful to analyze the driving force of urban expansion, which may provide us with a scientific basis to rationally utilize land resources, determining the law of urban development, researching the evolution process, predicting the urban expansion trends, and also providing guidance for the development of rational control policies.The Shenyang city was chosen as study area. Eight categories of land use types were extracted from remote sensing images (1997 and 2010) with ArcGIS software. Ten driving forces were chosen, including three natural factors, three distance factors, four social and economic factors. which were calculated based on the land use maps, DEM, topographic maps, zoning maps and the statistical yearbooks. The dependent variable was the change of built-up area of Shenyang from 1997 to 2010. Boosted regression trees (BRT) is an ensemble method and is a combination of techniques between statistical and machine learning traditions that has shown to be effective to identify relationships between results and influencing factors. Logistic regression is a method to discover the empirical relationships between a binary dependent and several independent categorical and continuous variables. Boosted Regression Trees and Logistic regression were used to analyze the main driving force of urban expansion synthetically.The result illustrated the relative influence of driving factors was followed by distance from urban area of 1997, distance from river, DEM, distance from highway and railway, land use types, development plan, GDP, population density, aspect, and slope based on BRT analysis. According to Logistic regression analysis, the relative influence of important factors was followed by development zone, distance from urban land of 1997, DEM, distance from highway and railway, population density, distance from river, rural residential areas and slope. The most important driving forces affecting the expansion of Shenyang are distance from urban area of 1997, DEM, distance from highway and railway. Meanwhile, they were all located in the top four of the main factors. The results revealed that the distance factors were the most important factors, and the total contribution rate of relative influence was up to 61.4%. It is demonstrated distance factors are the main driving forces of urban expansion. Natural factorswere less important, but the relative influence of DEM was important, and the contribution rate was 12.5%. Development zones and rural settlements are the only two factors have much influence in the socio-economic factors.On the whole, location factors, which refer to the distance from urban land in this study, were the leading factors of urban expansion. Natural factors, such as DEM, rivers and so on, are the basis of urban development, determining the overall urban spatial form. The construction of infrastructures, such as roads and railways, are the frame of the city. The social and economic factors decided the speed of urban expansion. Urban planning and development zone construction provided the direction of urban expansion.