With the acceleration of urban development and the transformation of industrial structure, the old industrial lot has become the focus of urban stock planning. However, the gradient of industrialization development in different regions of China is quite different, and there are many influencing factors. It is difficult to propose suitable renewal strategies for the renewal of old industrial lots in different cities because of the lack of scientific analysis methods. In recent years, with the rapid development of big data technology, the application of big data in urban planning is gradually mature, and it has become an effective means to analyze the law of social activities of urban residents and the characteristics of urban spatial aggregation. This paper creatively introduces big data analysis technology into the analysis of the spatial environment of the old industrial lot in the city, carries out visual analysis on the block vitality, traffic organization, functional formats and leisure space of the old industrial lot in Dongfeng Street, Daqing City, and finds the internal correlation between crowd flow and urban spatial vitality. In order to realize the sustainable renewal of the old industrial lot, the paper puts forward the renewal strategy of adjusting the nature of land use, optimizing service facilities, perfecting traffic organization and creating good places.
Published in | Science Discovery (Volume 11, Issue 6) |
DOI | 10.11648/j.sd.20231106.18 |
Page(s) | 243-260 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Big Data, Old Industrial Area, ArcGIS, Quantitative Analysis, Update
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APA Style
Guang, L., Jingwei, L. (2023). Research on the Renewal of Urban Old Industrial Lots Based on Big Data —— Take the Dongfeng Street Area of Daqing City as an Example. Science Discovery, 11(6), 243-260. https://doi.org/10.11648/j.sd.20231106.18
ACS Style
Guang, L.; Jingwei, L. Research on the Renewal of Urban Old Industrial Lots Based on Big Data —— Take the Dongfeng Street Area of Daqing City as an Example. Sci. Discov. 2023, 11(6), 243-260. doi: 10.11648/j.sd.20231106.18
@article{10.11648/j.sd.20231106.18, author = {Liu Guang and Li Jingwei}, title = {Research on the Renewal of Urban Old Industrial Lots Based on Big Data —— Take the Dongfeng Street Area of Daqing City as an Example}, journal = {Science Discovery}, volume = {11}, number = {6}, pages = {243-260}, doi = {10.11648/j.sd.20231106.18}, url = {https://doi.org/10.11648/j.sd.20231106.18}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20231106.18}, abstract = {With the acceleration of urban development and the transformation of industrial structure, the old industrial lot has become the focus of urban stock planning. However, the gradient of industrialization development in different regions of China is quite different, and there are many influencing factors. It is difficult to propose suitable renewal strategies for the renewal of old industrial lots in different cities because of the lack of scientific analysis methods. In recent years, with the rapid development of big data technology, the application of big data in urban planning is gradually mature, and it has become an effective means to analyze the law of social activities of urban residents and the characteristics of urban spatial aggregation. This paper creatively introduces big data analysis technology into the analysis of the spatial environment of the old industrial lot in the city, carries out visual analysis on the block vitality, traffic organization, functional formats and leisure space of the old industrial lot in Dongfeng Street, Daqing City, and finds the internal correlation between crowd flow and urban spatial vitality. In order to realize the sustainable renewal of the old industrial lot, the paper puts forward the renewal strategy of adjusting the nature of land use, optimizing service facilities, perfecting traffic organization and creating good places. }, year = {2023} }
TY - JOUR T1 - Research on the Renewal of Urban Old Industrial Lots Based on Big Data —— Take the Dongfeng Street Area of Daqing City as an Example AU - Liu Guang AU - Li Jingwei Y1 - 2023/12/08 PY - 2023 N1 - https://doi.org/10.11648/j.sd.20231106.18 DO - 10.11648/j.sd.20231106.18 T2 - Science Discovery JF - Science Discovery JO - Science Discovery SP - 243 EP - 260 PB - Science Publishing Group SN - 2331-0650 UR - https://doi.org/10.11648/j.sd.20231106.18 AB - With the acceleration of urban development and the transformation of industrial structure, the old industrial lot has become the focus of urban stock planning. However, the gradient of industrialization development in different regions of China is quite different, and there are many influencing factors. It is difficult to propose suitable renewal strategies for the renewal of old industrial lots in different cities because of the lack of scientific analysis methods. In recent years, with the rapid development of big data technology, the application of big data in urban planning is gradually mature, and it has become an effective means to analyze the law of social activities of urban residents and the characteristics of urban spatial aggregation. This paper creatively introduces big data analysis technology into the analysis of the spatial environment of the old industrial lot in the city, carries out visual analysis on the block vitality, traffic organization, functional formats and leisure space of the old industrial lot in Dongfeng Street, Daqing City, and finds the internal correlation between crowd flow and urban spatial vitality. In order to realize the sustainable renewal of the old industrial lot, the paper puts forward the renewal strategy of adjusting the nature of land use, optimizing service facilities, perfecting traffic organization and creating good places. VL - 11 IS - 6 ER -