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夜间灯光数据支持下的广州市人口空间化
引用本文:吴献文,速云中,孙照辉. 夜间灯光数据支持下的广州市人口空间化[J]. 测绘通报, 2021, 0(5): 59-62. DOI: 10.13474/j.cnki.11-2246.2021.0142
作者姓名:吴献文  速云中  孙照辉
作者单位:1. 广东工贸职业技术学院, 广东 广州 510510;2. 广州全成多维信息技术有限公司, 广东 广州 511457
基金项目:广东省教育厅普通高校重点科研平台(2020CJPT023);校级重点科研平台(2020-PT-01)
摘    要:了解区域人口的空间分布,能够为城市精细化管理和城市规划提供有力的支撑数据,对提高城市发展水平有重要的现实意义。为此,本文以“珞珈一号”(LJ-1 01)夜间灯光(NTL)影像为基础数据,以广州市为研究区,结合人口估算模型等方法,开展基于NTL数据的人口空间化研究。结果表明:LJ-1 01 NTL数据能够有效地应用于人口空间化研究。人口空间化后,广州市人口分布具有显著的“一主中心,多核心”的特征,各区域内部的人口分布差异可被清晰地展示与区分。本文结果对城市规划与城市管理具有一定价值的辅助支撑作用。

关 键 词:珞珈一号  夜间灯光数据  人口空间化  人口估算模型  广州市  
收稿时间:2020-12-07
修稿时间:2021-03-17

Spatialization of population in Guangzhou supported by nighttime light data
WU Xianwen,SU Yunzhong,SUN Zhaohui. Spatialization of population in Guangzhou supported by nighttime light data[J]. Bulletin of Surveying and Mapping, 2021, 0(5): 59-62. DOI: 10.13474/j.cnki.11-2246.2021.0142
Authors:WU Xianwen  SU Yunzhong  SUN Zhaohui
Affiliation:1. Guangdong Polytechnic of Industry and Commerce, Guangzhou 510510, China;2. Guangzhou Quanchengjituan Duowei Information Technology Co., Ltd., Guangzhou 511457, China
Abstract:Understanding the spatial distribution of population can provide data to support urban management and urban planning, which is of great practical significance for improving urban development. Therefore, this study uses the nighttime light (NTL) image of LJ-1 01 as the basic data, Guangzhou as the study area, and combines the population estimation model and other methods to carry out a study of population spatialization based on NTL data. The results show that the LJ-1 01 NTL data can be effectively applied to the study of population spatialization. After population spatialization, the population distribution in Guangzhou has a distinctive feature of “one main center, multiple cores”, and the differences in population distribution within each area can be clearly shown and distinguished. The results of this study can be of some value in supporting urban planning and urban management.
Keywords:LJ-1 01  nighttime light data  population spatialization  population estimation model  Guangzhou city  
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