基于多源数据的城市中心体系识别与评估 *#br#——以南京为例

摘要　塑造对城市结构的清晰认知是城市中心体系研究展开的基础,但目前的城市中心体系识别方法却仍存在精度差、成本高、维度单一等多方面的问题。在梳理中心体系理论研究成果的基础上,发现城市中心体系主要存在人、地、业三种形式的表征。运用大数据的空间辅助分析技术洞悉三要素的实际分布情况,能更准确地识别城市中心体系的分布状态,并根据三要素的分布及强度分级情况,针对中心体系的局部板块进行精细化的剖析研究,多角度阐述了中心体系不仅仅是单一维度的中心,而是由多种要素共同支撑的有机整体。尝试构建了基于多源大数据的城市中心体系测度的理论及技术方法框架,并以南京为例探讨技术方法的可行性,使其在面向不断创新发展的城市中心体系的理论和实践时,可以进一步拓展和调整,以适应不同情境的需求。

Identification and Evaluation of Urban Centre Systems Based on Multi-source #br#Big Data: Using Nanjing as an Example

ABSTRACT　A clear understanding of urban structures is the basis for this research of urban centre systems. However, there are many problems with the identification methods for the current urban centre systems, such as low precision, high costs, and a single dimension. Sorting the existing research on urban centre systems revealed they can be characterized by people distribution, urban morphology and industry. Spatial-aided analysis technology based on big data helps us understand the actual distribution situation of the three elements, and enables more accurate identification of the distribution state of urban centre systems. Based on the distribution and distribution degree of each element, a detailed analysis was performed on the local sections of central systems, and showed that urban centre systems are not only the centre of a single dimension, but rather an organic whole supported by multiple elements. With Nanjing city as an example, this paper explores the feasibility of technical methods, and attempts to build a theoretical framework for the technical method of urban centre system measurements, based on multi-source big data. Further expansion and adjustment of the theory and practice of urban centre systems would allow continuous innovation and development to adapt to the needs of different situations.