沿海发达地区小城镇城乡建设用地变化及驱动力研究——以宁波市奉化溪口镇为例

基于奉化溪口镇1990~2015年6期土地利用数据, 借助土地利用转移矩阵、城乡建设用地扩展速度、土地利用动态度、土地利用结构信息熵、核密度和Logistic回归模型等方法, 探析奉化溪口镇城乡建设用地变化特征和驱动因子. 结果表明: (1)1995~2015年, 溪口镇城乡建设用地规模不断扩大, 增长速度不稳定, 城镇用地、农村居民点用地和其他建设用地增长各具特点; (2)建设用地信息熵持续增加, 土地类型趋于复杂化、有序化; (3)城乡建设用地的转入面积远大于转出面积, 主要转入来源为耕地和林地; (4)城乡建设用地核密度高值区集聚于城镇的东北部, 核密度分布特征随时间变化不明显; (5)建设用地分布主要受社会经济因素的影响, 其中地均国内生产总值、人口密度、高程值与距河流距离影响较大.

Urban and rural construction land changes and the driving factors for small towns in developed coastal areas: A case study of Xikou town in Fenghua

It is of great significance to explore the changes in urban and rural construction land and their driving forces for coordinating the allocation of urban and rural land resources. Based on the 6-stage land use data from year 1990 to 2015, the modeling methods of land involves using the transfer matrix, urban and rural construction land expansion rate, dynamics and structure information entropy of land use, kernel density. Also, the logistic regression is used to explore the changing characteristics and driving factors of Xikou town in Fenghua District of Ningbo City. The results reveal that: (1) From year 1995 to 2015, the total area of urban and rural construction land in Xikou town has been expanding, and the expanding rate is far away from a constant. The growth scale varies as manifested in urban land, rural residential land and other construction land; (2) The information entropy of construction land keeps growing up, and the land types tend to be more diversified with a certain pattern; (3) The influx area of urban and rural construction land is much larger than that of the outbound area, and the primary sources of influx area are cultivated land and forest land; (4) High-value areas of kernel density of urban and rural construction land are mainly concentrated in towns located in the northeast, and the distribution characteristics of kernel density remain stable in time; (5) The distribution of urban and rural construction land is greatly affected by the GDP per land area, population density, added value and the distance from river, showing that the socioeconomic conditions are the main influencing factors.