Research on the Renewal of Urban Old Industrial Lots Based on Big Data —— Take the Dongfeng Street Area of Daqing City as an Example

Liu Guang; Li Jingwei

doi:doi:10.11648/j.sd.20231106.18

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Research on the Renewal of Urban Old Industrial Lots Based on Big Data —— Take the Dongfeng Street Area of Daqing City as an Example

Liu Guang, Li Jingwei

Published in Science Discovery (Volume 11, Issue 6)

Received: 19 November 2023 Accepted: 5 December 2023 Published: 8 December 2023

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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.

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), 2024. Published by Science Publishing Group

Keywords

Big Data, Old Industrial Area, ArcGIS, Quantitative Analysis, Update

References

[1]	杨俊宴, 曹俊. 动•静•显•隐: 大数据在城市设计中的四种应用模式 [J]. 城市规划学刊, 2017 (04): 39-46.
[2]	Batty M. Big data, smart cities and city planning [J]. Dialogues in Human Geography, 2013, 3 (3): 274-279.
[3]	Rathore M M, Ahmad A, Paul A, etal. Urban planning and building smart cities based on the Internet of Things using Big Data analytics [J]. Computer Networks the International Journal of Computer & Telecommunications Networking, 2016, 101 (C): 63-80.
[4]	Bibri, Elias S. [The Urban Book Series] Smart Sustainable Cities of the Future \|\| Sustainable Urban Forms: Time to Smarten up with Big Data Analytics and Context–Aware Computing for Sustainability [J]. 2018.
[5]	Pentsev, E & Makarova, O. (2019). Big data in urban planning and territory management. IOP Conference Series: Materials Science and Engineering. 481. 012026. 10. 1088/1757-899X/481/1/012026.
[6]	高原, 陆晓东. 大数据背景下的广州历史文化街区活力定量研究 [J]. 中国名城, 2020 (07): 53-61. DOI: 10. 19924/j. cnki. 1674-4144. 2020. 07. 008.
[7]	党安荣, 许剑, 甄茂成. 大数据在城市规划中的应用研究综述 [J]. 地理信息世界, 2019, 26 (1): 8.
[8]	李芏. 基于大数据的南宁历史街区保护与更新研究 [D]. 广西大学, 2016.
[9]	Weilacher U. Between Landscape Architecture and Land Art [M]. Springer Verlag, 1996.
[10]	Kirsten Jane Robinson, 王洪辉. 探索中的德国鲁尔区城市生态系统: 实施战略 [J]. 国外城市规划, 2003, 18 (6): 3-25.
[11]	任凌奇, 郑重. 非保护类工业地段城市设计的逻辑构建——以杭州民生药厂地块为例 [J]. 规划师, 2020, 36 (23): 32-37.
[12]	刘刚. 工业遗产与历史城市地段的空间形态整合 [D]. 南京大学, 2019.
[13]	顾家碧, 费腾. 大数据技术在历史街区空间品质更新中的应用 [J]. 建筑与文化, 2020, No. 195 (06): 70-71.
[14]	黄一琦, 许俊萍. 基于大数据的零售业空间热点识别及人口分布特征分析——以厦门市为例 [J]. 中外建筑, 2020 (12): 107-111.
[15]	互联网数据分析方法 -《大学生论文联合库》-2016.
[16]	闵忠荣, 丁帆. 基于百度热力图的街道活力时空分布特征分析——以江西省南昌市历史城区为例 [J]. 城市发展研究, 2020 (2).
[17]	李凤仪, 李方正. 大数据在绿地规划设计中多尺度应用进展综述 [J]. 西部人居环境学刊, 2019, 34 (05): 63-71.
[18]	Qi Shi. Mohamed Abdel-Aty. Big Data applications in real-time traffic operation and safety monitoring and improvement on urban expressways [J]. Transpotation Research Part C. 2015. 58: 380 394.
[19]	郝新华. 基于多源数据的奥林匹克森林公园南园使用状况评估 [C]. 中国城市规划学会, 沈阳市人民政府. 规划60年: 成就与挑战——2016 中国城市规划年会论文集 (11 风景环境规划). 北京: 中国建筑工业出版社, 2016: 10.
[20]	Jacobs J. The Death and Life of Great American Cities [M]. Random House LLC, 1916.
[21]	刘颂, 李春晖, 赖思琪. 上海市环城绿带的游憩转型潜力分析及策略 [J]. 上海城市规划, 2019 (03): 77-83.
[22]	郭琪, 朱京海. 工业遗存概论 [M]. 辽宁科学技术出版社, 2011.
[23]	姚炜. 欠发达地区资源型城市工业区更新策略研究 [D]. 东南大学, 2019.

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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

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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

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AMA 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

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@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}
}

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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  -

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Author Information

Liu Guang

MCC Huatian Engineering Technology Co., Ltd., Nanjing, China

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Li Jingwei

College of Civil Engineering and Architecture, Northeast Petroleum University, Daqing, China

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Plain Text BibTeX RIS

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

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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

Copy | Download

AMA 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

Copy | Download

@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}
}

Copy | Download

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  -

Copy | Download