Artificial Intelligence and Landscape Architecture: The Aesthetic and Sustainable Fabric of The Future

Authors

DOI:

https://doi.org/10.53463/ecopers.20240313

Keywords:

Artificial intelligence, Data analysis, Environmental sensitivity, Landscape architecture, Sustainability

Abstract

This article examines the impact of artificial intelligence on the field of landscape architecture and discusses its potential role in shaping aesthetic and sustainable designs in the future. It addresses the contributions of AI technologies to big data analytics, environmental sensitivity, sustainability, and functional landscape designs. The study highlights the potential of artificial intelligence to provide innovative and sustainable solutions within landscape architecture.

References

Alpaydin, E. (2020). Introduction to machine learning. Cambridge: MIT Press.

Aldrich, R., & Stearns, M. (2017). The role of climate data in landscape design. Journal of Environmental Planning, 15(2), 80-89.

Andersson, A. (2020). Plant selection and landscape ecology: Innovations in practice. Landscape Architecture Review, 12(1), 42-58.

Andersson, E. (2020). Sustainability and landscape architecture: New directions. Landscape Journal, 39(1), 45-58.

Andersson, H. (2020). Artificial intelligence and its applications in landscape architecture. Journal of Landscape Architecture, 15(3), 42-48.

Andersson, M. (2020). Artificial intelligence in landscape design: Strategies for sustainable development. Journal of Landscape Architecture, 25(4), 42-50.

Bennett, L., & Palmer, S. (2018). Predicting plant performance using artificial intelligence. Horticultural Science, 25(3), 75-85.

Benson, D. (2021). The role of artificial intelligence in sustainable landscape architecture. Journal of Environmental Management, 271, 77-90.

Benson, M. (2021). Awareness and understanding of artificial intelligence in landscape design. Landscape Research, 46(2), 76-80.

Benson, R. (2021). Sustainable landscape architecture: Principles and practices. New York: Springer.

Bertoldi, P., & Atanasiu, B. (2010). Energy efficiency in the EU: A statistical analysis. Brussels: European Commission.

Brady, N. C., & Weil, R. R. (2016). The nature and properties of soils (15th ed.). Pearson.

Chen, X., Zhang, Y., & Wang, J. (2018). Big data analytics for sustainable development. Sustainable Cities and Society, 41, 84-95.

Chien, S., & Ding, Y. (2017). Predictive analytics for carbon emission reduction: An overview. Journal of Cleaner Production, 149, 53-61.

Dua, D., & Graff, C. (2017). UCI machine learning repository. Irvine: University of California.

Garcia, A., Lee, J., & Smith, T. (2019). Challenges and opportunities in the adoption of AI in landscape design. Landscape Review, 23(2), 95-103.

Garcia, E., López, R., & Torres, J. (2019). The impact of artificial intelligence on landscape architecture education: Challenges and opportunities. Landscape Journal, 38(1), 95-105.

Garcia, J., López, A., & Martinez, C. (2019). AI for environmental monitoring: Innovations and applications. Environmental Science & Technology, 53(3), 99-108.

Garcia, P., Thompson, L., & Lee, J. (2019). Education strategies for landscape architects in the age of AI. Landscape Journal, 38(1), 95-102.

Gartner, T., Patel, A., & Thomas, M. (2018). Modeling carbon emissions in sustainable design. Renewable Energy, 122, 62-71.

Han, J., Kamber, M., & Pei, J. (2011). Data mining: Concepts and techniques. Amsterdam: Elsevier.

Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction. New York: Springer.

Johnson, R. (2020). Future trends in landscape architecture and artificial intelligence. International Journal of Landscape Architecture, 15(4), 58-72.

Johnson, R. (2020). Interactive workshops on AI: A new approach for designers. Design Studies, 41, 55-64.

Kang, J., Li, X., & Zhang, Y. (2018). Intelligent irrigation management system for precision agriculture. Computers and Electronics in Agriculture, 148, 99-107.

Kang, Y., & Lu, Y. (2019). Smart resource management systems: The role of artificial intelligence. Journal of Environmental Management, 231, 111-120.

Kim, J. (2018). Optimizing plant placement strategies in landscape architecture. International Journal of Landscape Design, 9(4), 40-49.

Kim, J. (2018). Innovative trends in landscape architecture: The role of AI technologies. Landscape and Urban Planning, 175, 40-50.

Kim, S. (2018). Aesthetic dimensions of landscape architecture in the age of AI. Journal of Urban Design, 23(1), 44-56.

Kibert, C. J. (2016). Sustainable construction: Green building design and delivery. Hoboken: Wiley.

Li, H., & Zhao, X. (2017). Artificial intelligence in plant selection for urban landscapes. Urban Ecosystems, 20(1), 110-115.

Li, X., & Li, Y. (2018). Predictive models for landscape planning. Journal of Environmental Management, 213, 132-143.

Li, X., & Zhao, Y. (2017). AI applications in water resource management for landscape architecture. Water Science and Technology, 76(2), 112-120.

Liu, S., Zhang, L., & Wu, Y. (2015). Soil fertility simulations for landscape projects. Journal of Soil and Water Conservation, 70(5), 72-80.

Mousazadeh, H., Pourbakhsh, P., & Zadeh, A. (2020). Renewable energy integration through AI. Journal of Renewable Energy, 30(1), 21-34.

O'Sullivan, A. (2016). Emerging technologies in landscape architecture. Landscape Architecture Frontiers, 4(3), 12-19.

Pfeifer, A., & Pape, M. (2020). Criteria for plant selection in sustainable landscape design. Landscape Research, 45(2), 100-110.

Rutherford, A. (2014). Simulation modeling and analysis. Mathematical Modeling and Simulation, 7(2), 54-67.

Smith, A. (2019). The future of landscape architecture: Integrating AI and design practices. Landscape Architecture Review, 22(2), 55-65.

Smith, J. (2019). Artificial intelligence: The next frontier in landscape design. Design Studies, 30(2), 60-70.

Smith, J. (2019). Innovative uses of AI in landscape design. International Journal of Landscape Architecture, 10(4), 57-65.

VanderMeulen, V., & Kelly, J. (2017). Smart waste management solutions: An AI approach. Waste Management, 62, 65-72.

Wang, S., & Zhang, H. (2020). AI for water quality monitoring: Innovations and applications. Environmental Monitoring and Assessment, 192(3), 68-78.

Wang, Y., & Li, J. (2016). Simulation of resource utilization in construction projects using AI techniques. Automation in Construction, 69, 79-86.

Zhang, W., Liu, Q., & Xu, H. (2019). Artificial intelligence in energy efficiency analytics. Energy Reports, 5, 73-80.

Zhou, H., & Wang, L. (2018). Predictive modeling in landscape design: The contribution of AI. Computers, Environment and Urban Systems, 67, 25-35.

Zhou, J., & Wang, T. (2018). Data-driven landscape architecture: The role of big data. Journal of Landscape Architecture, 13(2), 33-45.

Published

23-12-2024

How to Cite

Kayan, M. (2024). Artificial Intelligence and Landscape Architecture: The Aesthetic and Sustainable Fabric of The Future. Ecological Perspective, 4(1), 55–72. https://doi.org/10.53463/ecopers.20240313

Issue

Section

Review Articles