中文摘要：

城市地价是一个具有时空性质的多维概念，随着土地市场的日渐发育，地价成为土地市场运作的重要信息和价值判断标准，而城市基准地价的更新速度慢，不能及时、准确地反映城市的地价水平和地价动态分布规律。与此同时，城市地价动态监测点的地价信息能够分年度及时、准确的更新。因此，利用地价动态监测样点的地价信息，快速、及时的分析地价的空间结构特征、时空演变趋势成为当今土地管理中值得深入探讨的课题。本文以南京市主城区为研究区域，以住宅地价为研究对象，依托南京市地价动态监测和土地市场交易数据，在探索性空间数据分析（ESDA）和地统计学方法的支持下，建立了2001年-2004年南京市主城区住宅用地数字地价模型，从宏观层面上，研究了整个区域的住宅地价空间演化趋势，从中观层面上，选取典型地价剖面研究了住宅地价的时间演化趋势，以期及时、准确的掌握城市的地价水平和地价动态分布规律，为政府调节土地市场起到一定的借鉴作用。

英文摘要：

Urban land value is a multidimensional concept development of land market, urban land price is looked as a value judgment of land market operation. Because the veloci with the spatio-temporal property. With the piece of important information and standard of ty of updating the datum land price is slow, it can not show the dynamic distribution pattern of urban land price on time. At the same time, the information of dynamic monitoring point of urban land price can be updated correctly and timely for each year. Consequently, we can analyze spatial distribution pattern and evolution of spatial structure based on the information of dynamic monitoring point of urban land price. Taking the downtown areas of Nanjing City as study area and using the residential land price as study object, and with the land rent theory, land price theory, location theory, spatial structure model of land value as study basis, the author analyzes the data from dynamic monitoring point of residential land price and builds residential land price database of nanjing city from 2001 to 2004. In this paper, the author gets the analysis result of dynamic monitoring point of residential land price by applying exploratory spatial data analysis method, and builds digital residential land price model from 2001 to 2004 based on spatial interpolation methods such as Kriging, which lays a solid foundation for spatial analysis of residential land price. Subsequently, in order to acquire dynamic land price distribution rule and provide support for government to adjust land market, the author summarizes the spatial structure characteristics of residential land price, and studies spatial evolution trend of study area in macroscopic view. On the other hand, the author studies temporal evolution trend of residential land price by choosing typical residential land price profile in a microscopic view.