Spatial Structure Identification of Urban Agglomeration in Liaoning Province Based on Luminous Data and Graph Theory

Zhiwei Xie, Ruizhao Liu, Chao Huang, Guangming Song
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Abstract

In order to be able to describe the boundary and evolution of urban agglomeration in Liaoning in real time and quantitatively, this paper designs and implements a method to identify the spatial structure of urban agglomeration based on nighttime light data and graph theory. The neighborhood extreme value method is used to identify the feature points, and the hydrological analysis method is used to indirectly extract the feature lines, then construct the nighttime light intensity map. The innovative graph theory is applied to the node clustering set detection of the nighttime light intensity map, and the agglomeration characteristics of cities are discovered by establishing the geographic mapping relationship between nodes and cities. In this paper, major cities in Liaoning, China, are taken as the study area, and NPP/VIIRS (NPOESS Preparatory Project/Visible Infrared Imaging Radiometer) data in 2016 and 2020 are used. The experimental results prove that the development momentum of southern Liaoning is stronger, the central Liaoning absorbs part of the western Liaoning, and the western Liaoning further shrinks.
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基于发光数据和图论的辽宁省城市群空间结构识别
为了能够实时定量地描述辽宁城市群的边界及其演化,本文设计并实现了一种基于夜间灯光数据和图论的城市群空间结构识别方法。利用邻域极值法识别特征点,利用水文分析方法间接提取特征线,构建夜间光强图。将创新的图论应用于夜间光强图的节点聚类集检测,通过建立节点与城市的地理映射关系,发现城市的集聚特征。本文以中国辽宁省主要城市为研究区域,使用2016年和2020年NPP/VIIRS (NPOESS筹备项目/可见光红外成像辐射计)数据。实验结果证明,辽南地区发展势头较强,辽中地区吸收了部分辽西地区,辽西地区进一步萎缩。
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