Spatial Pattern Analysis of Zhuhai Urban Development Based on POI Big Data
- DOI
- 10.2991/978-94-6463-064-0_82How to use a DOI?
- Keywords
- POI big data; Baidu Huiyan; spatial pattern; Zhuhai city
- Abstract
This study is to obtain accurately the urban development & evolution characteristics and spatial development pattern information of Zhuhai, to analyze its urban development laws by using spatio-temporal big data, to improve its scientific entity and effectiveness of planning, as well as to help its urban construction and development. It makes research to the population density, catering service facilities and spatial distribution characteristics of work and residence in Zhuhai with Baidu Huiyan data and from the time-space macro analysis of the urban development of the whole city to the specific evaluations of people, land and things in the dimensions of districts, counties and streets. It aims to explore the internal texture, spatial pattern and evolution law of Zhuhai urban development. It proves that Baidu Huiyan big data under scientific mining and processing can not only provide a more dynamic perspective and method for urban space research, but also provide a good analysis and expression way for the facility planning and evaluation in the future urban planning.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Zili Zhao AU - Xiupeng Zhang AU - Zhi’ao Zhang AU - Xintao Peng PY - 2022 DA - 2022/12/27 TI - Spatial Pattern Analysis of Zhuhai Urban Development Based on POI Big Data BT - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022) PB - Atlantis Press SP - 794 EP - 807 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-064-0_82 DO - 10.2991/978-94-6463-064-0_82 ID - Zhao2022 ER -