测绘通报 ›› 2025, Vol. 0 ›› Issue (5): 165-171.doi: 10.13474/j.cnki.11-2246.2025.0527

• 技术交流 • 上一篇    

区域地下管线空间分异特征探究

秦旭寰1,2, 谢文瑄1,2, 孔令彦1,2, 张晟源1,2, 韩帅1,2, 岳林峰1,2, 谢一茹1,2   

  1. 1. 北京市测绘设计研究院, 北京 100038;
    2. 城市空间信息工程北京市重点实验室, 北京 100038
  • 收稿日期:2024-10-16 发布日期:2025-06-05
  • 通讯作者: 孔令彦。E-mail:kongly@163.com
  • 作者简介:秦旭寰(1996—),女,硕士,工程师,研究方向为空间分析与地学统计。E-mail:2016301110009@whu.edu.cn
  • 基金资助:
    北京市科技计划“揭榜挂帅”项目:城市智慧管网“观、管、防”一体化关键技术研发与示范应用(Z231100003823023)

Exploration of spatial differentiation characteristics of regional underground pipelines

QIN Xuhuan1,2, XIE Wenxuan1,2, KONG Lingyan1,2, ZHANG Shengyuan1,2, HAN Shuai1,2, YUE Linfeng1,2, XIE Yiru1,2   

  1. 1. Beijing Institute of Surveying and Mapping, Beijing 100038, China;
    2. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 100038, China
  • Received:2024-10-16 Published:2025-06-05

摘要: 本文基于地理信息空间分析和数理统计法,以北京市南部某区为研究对象,依托研究区内供水、中水、降水、污水、燃气、热力、电力、通信和广播电视9类地下管线数据,分析了地下管线数据的空间规划设计特征。研究发现:①根据Pearson相关系数,该区各专业地下管线呈“南疏北密,由城区中心向外辐射”的空间分布特征;②由全局和局部Moran's I和Getis-Ord Gi*指数可知,该区管线在空间上形成了西北-东南向“一高一低”两个集聚区和一个显著分散趋势,且冷热点分布与空间集聚模式基本相同,具有空间依赖关系;③城区内各街道的管线覆盖率明显高于南部乡镇,呈显著两极分化。本文可为该区地下管线管理与规划提供重要的空间分析依据和实证数据支持,为提升地下空间的可持续利用、保障地下空间高质量发展、优化基础设施布局提供参考和指导。

关键词: 地下管线, 空间自相关, 热点分析, 空间格局, GIS

Abstract: Based on geographic information spatial analysis and mathematical and statistical methods, this study takes a district in the south of Beijing as the research object, relies on data from nine types of underground pipelines, including water supply, reclaimed water, stormwater, sewage, gas, heating, electricity, telecommunications, and broadcasting, to analyze the spatial planning and design characteristics of these pipelines. The study finds that: ① According to the Pearson correlation coefficient, the underground pipelines of various specializations in the district exhibit a spatial distribution pattern of “sparser in the south and denser in the north, radiating outward from the center.” ②Based on the global and local Moran's I and Getis-Ord Gi* indices, the pipelines in the district form two clusters of “high and low” along a northwest-southeast axis and one area with a significant dispersion trend. The distribution of cold and hot spots is largely consistent with the spatial clustering pattern, indicating a spatial dependency. ③The pipeline coverage in urban streets is significantly higher than in southern townships, showing a pronounced polarization. This study can provide important spatial analysis foundations and empirical data support for the management and planning of underground pipelines in the district, offering reference and guidance for enhancing the sustainable use of underground space, ensuring high-quality development of underground spaces, and optimizing infrastructure layout.

Key words: underground pipelines, spatial autocorrelation, hotspot analysis, spatial pattern, GIS

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