Impact of Agricultural Big Data Analysis on Urban Development

Authors

  • Gaofeng Wu Graduate School, University of the East, Manila, Philippines and College of Science and Technology, Jiaozuo Normal College, Jiaozuo, China Author
  • Henry Dyke A. Balmeo University of the East, Manila, Philippines Author

DOI:

https://doi.org/10.62677/IJETAA.2407122

Keywords:

Agricultural big data analysis, Urban development, Decision support

Abstract

As an emerging technological approach, agricultural big data analysis provides new possibilities for urban development. This paper systematically elaborates on the applications of agricultural big data analysis in optimizing urban development, improving resource utilization, and enhancing urban environmental sustainability. It explores the impact of agricultural big data analysis on urban development. The paper describes the current state of agricultural big data analysis in Jiaozuo City in detail and, through detailed case studies, such as using the support vector machine (SVM) model to optimize irrigation water, the results indicate a reduction of 34.75 m3/ha in total water consumption and an average reduction of 5.79 m3/ha per sample. By calculating the optimal path of the agricultural product supply chain using the ant colony algorithm, the shortest and longest distribution paths of the agricultural product supply chain planned in this paper differ by 200%. The research shows that agricultural big data analysis significantly optimizes resource allocation, promotes the coordinated development of cities and agriculture, ensures the safety of urban resources such as food, and supports the sustainable development of cities. Finally, suggestions are made for further exploration in this field by the government, enterprises, and research institutions. The development of this technology can provide innovative solutions for urban development.

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References

J. Xu, J. Wang, and J. Liu, “Research on the path of high-quality development of smart agriculture driven by big data technology,” Agricultural Economy, no. 04, pp. 23–24, 2024.

X. Ma and X. Yang, “Promote the formation of new quality productivity to drive the high-quality development of agriculture,” Agricultural Economic Issues, no. 04, pp. 4–12, 2024.

C. Feng, “Influencing factors and advancement paths of high-level digital government construction,” Journal of Hebei University (Philosophy and Social Science), vol. 47, no. 06, pp. 117–130, 2022.

X. Li, M. Chen, “China’s rural digital transformation: Measurement, regional differences and promotion path,” Agricultural Economic Issues, no. 11, pp. 89–104, 2023.

C. Chen, Y. Zhao, How digital empowerment promotes high-quality supply of rural public services - A case study of the For Village” platform in Taoba Village, Qionglai City, Sichuan Province,” Agricultural Economic Issues, no. 12, pp. 47–59, 2023.

Y. Zhang, M. Feng, F. Yi, “Logic, dilemma and approach of rural environmental digital governance from the perspective of multi-center governance,” Agricultural Economic Issues, no. 03, pp. 36–53, 2024.

L. Su, “Digital governance promotes the improvement of rural governance efficiency: Key challenges, logical framework and policy optimization,” Agricultural Economic Issues, pp. 1–18, 2024.

Y. Zhou, W. Zhang, “Thoughts on spatio-temporal big data assisting rural revitalization,” Surveying and Spatial Geographic Information, vol. 47,no. 04, pp. 15–17+21, 2024.

X. Li, “Research on the development path of digital agriculture under the background of rural revitalization,” Smart Agriculture Guide, vol. 4,no. 05, pp. 5–8, 2024.

X. Jing, Y. Shi, “Compressed storage scheme of agricultural Internet of Things data with high value density based on blockchain,” Transactions of the Chinese Society of Agricultural Engineering, vol. 40, no. 02, pp.273–282, 2024.

X. Yu, “Institutional innovation of farmers’ protection in digital agriculture,” Journal of Northeast Normal University (Philosophy and Social Sciences), no. 01, pp. 126–136, 2024.

M. Shen, L. Xing, “Impact of environmental regulation on the income of urban agricultural migrant population - Evidence from micro survey data,” Urban Problems, no. 11, pp. 46–54+65, 2023.

Q. Zhang, Q. Lin, S. Mao, “Exploring the path of China’s smart agriculture development from an international perspective,” World Agriculture, no. 08, pp. 17–26, 2022.

Y. Guo, Q. Xiao, Z. Zhou, “International comparative analysis of agricultural support level and policy structure changes - Based on the investigation of EU, US, Australia, Japan, South Korea, Brazil, and China,” World Agriculture, no. 01, pp. 17–29, 2023.

X. Yuan, E. Huang, “EU smart agriculture development experience and its enlightenment,” World Agriculture, no. 05, pp. 27–36, 2022.

Y. Che, X. Hui, Y. Li, et al., “Simulation of deep mining of agricultural production data considering environmental parameters,” Computer Simulation, pp. 1–6, 2024

Impact of Agricultural Big Data Analysis on Urban Development

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Published

2024-08-25

How to Cite

[1]
G. Wu and H. D. A. Balmeo, “Impact of Agricultural Big Data Analysis on Urban Development”, ijetaa, vol. 1, no. 7, pp. 1–7, Aug. 2024, doi: 10.62677/IJETAA.2407122.

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