Innovative Applications of Artificial Intelligence in Agricultural Land Planning

Authors

  • Peng Li

DOI:

https://doi.org/10.54691/beer5c47

Keywords:

Intelligent Agriculture; Artificial Intelligence; Sustainability; Information Identification.

Abstract

This paper reviews the diverse applications of Artificial Intelligence (AI) in agricultural land planning, highlighting how AI enhances agricultural production efficiency, optimizes resource allocation, and strengthens decision-making quality to promote sustainable agriculture. The article discusses AI's role in land suitability analysis, precision agriculture, integration into decision support systems, and the challenges and limitations of technology, emphasizing AI's significant role in advancing sustainable agricultural development and future research directions. Despite challenges such as data quality, model transparency, and ethical issues, AI's application prospects remain broad, potentially becoming a significant driving force in agricultural land planning and global food security.

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References

Patel A, Kethavath A, Kushwaha NL, Naorem A, Jagadale M, K.R S, et al. Review of artificial intelligence and internet of things technologies in land and water management research during 1991–2021: A bibliometric analysis. Engineering Applications of Artificial Intelligence. 2023; 123:106335.

Javaid M, Haleem A, Khan IH, Suman R. Understanding the potential applications of Artificial Intelligence in Agriculture Sector. Advanced Agrochem. 2023;2(1):15-30.

Ruiz I, Pompeu J, Ruano A, Franco P, Balbi S, Sanz MJ. Combined artificial intelligence, sustainable land management, and stakeholder engagement for integrated landscape management in Mediterranean watersheds. Environmental Science & Policy. 2023;145:217-27.

Alaoui ME, Amraoui KEL, Masmoudi L, Ettouhami A, Rouchdi M. Unleashing the potential of IoT, Artificial Intelligence, and UAVs in contemporary agriculture: A comprehensive review. Journal of Terramechanics. 2024;115:100986.

Zhou H, Na X, Li L, Ning X, Bai Y, Wu X, et al. Suitability evaluation of the rural settlements in a farming-pastoral ecotone area based on machine learning maximum entropy. Ecological Indicators. 2023;154:110794.

Pandit S, Shimada S, Dube T. Comprehensive Analysis of Land Use and Cover Dynamics in Djibouti Using Machine Learning Technique: A Multi-Temporal Assessment from 1990 to 2023. Environmental Challenges. 2024:100920.

Sun Y, Li Y, Wang R, Ma R. Modelling potential land suitability of large-scale wind energy development using explainable machine learning techniques: Applications for China, USA and EU. Energy Conversion and Management. 2024;302:118131.

Liu Y, Huang X, Liu Y. Detection of long-term land use and ecosystem services dynamics in the Loess Hilly-Gully region based on artificial intelligence and multiple models. Journal of Cleaner Production. 2024;447:141560.

Sachithra V, Subhashini LDCS. How artificial intelligence uses to achieve the agriculture sustainability: Systematic review. Artificial Intelligence in Agriculture. 2023;8:46-59.

Mandal S, Yadav A, Panme FA, Devi KM, Kumar S.M S. Adaption of smart applications in agriculture to enhance production. Smart Agricultural Technology. 2024;7:100431.

Chandel NS, Chakraborty SK, Chandel AK, Dubey K, A S, Jat D, et al. State-of-the-art AI-enabled mobile device for real-time water stress detection of field crops. Engineering Applications of Artificial Intelligence. 2024;131:107863.

Islam MM, Talukder MA, Sarker MRA, Uddin MA, Akhter A, Sharmin S, et al. A deep learning model for cotton disease prediction using fine-tuning with smart web application in agriculture. Intelligent Systems with Applications. 2023;20:200278.

Hu T, Zhang X, Bohrer G, Liu Y, Zhou Y, Martin J, et al. Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield. Agricultural and Forest Meteorology. 2023;336:109458.

Khan MS, Shoaib A, Arledge E. How to promote AI in the US federal government: Insights from policy process frameworks. Government Information Quarterly. 2024;41(1):101908.

Dhanush G, Khatri N, Kumar S, Shukla PK. A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce. Scientific African. 2023;21:e01798.

Abulibdeh A, Zaidan E, Abulibdeh R. Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production. 2024;437:140527.

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Published

2024-06-23

Issue

Section

Articles

How to Cite

Li, P. (2024). Innovative Applications of Artificial Intelligence in Agricultural Land Planning. Frontiers in Science and Engineering, 4(6), 75-81. https://doi.org/10.54691/beer5c47