Research Article

Text to Image in Landscape Architecture: Artificial Intelligence Approaches

Volume: 18 Number: 4 July 15, 2025
TR EN

Text to Image in Landscape Architecture: Artificial Intelligence Approaches

Abstract

Generating ideas for designing spaces with creative and diverse concepts in landscape architecture design is a time-consuming process. With technological advancements, effective use of time has become increasingly significant, and applications that produce creative, realistic, and elaborate visuals from text in the field of artificial intelligence (AI) have attracted attention. However, the use of AI applications in landscape architecture raises many questions regarding the rapid and accurate development of design ideas through the Text-to-Image (T2I) method: how satisfying are AI-generated visuals in terms of professional accuracy and aesthetics? Can AI accurately perceive professional terms? What is the general relationship between AI and landscape architecture? Apart from coming up with an answer to these questions, this study aims to investigate the potential of text-to-image (T2I) models in generating design concepts for landscape architecture. Fifty professional terms were selected and used to create 70-word prompts across six distinct design concepts. Four popular T2I models (Dall-E, MidJourney, LookX, and mnml) were employed to generate visuals based on these prompts. The images generated were evaluated based on their adherence to professional standards, aesthetic appeal, creativity, and technical accuracy. Results indicated that while AI models could effectively interpret a wide range of professional terms, including abstract and highly technical concepts, there were limitations in capturing the nuanced details of landscape design. This study highlights the potential of AI to assist landscape architects in the early stages of the design process, but also underscores the need for human expertise to refine and optimize AI-generated designs. Future research should explore ways to improve the accuracy and specificity of AI-generated landscape designs, as well as investigate the potential of integrating AI with other design tools and techniques.

Keywords

References

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Details

Primary Language

English

Subjects

Landscape Design

Journal Section

Research Article

Publication Date

July 15, 2025

Submission Date

November 20, 2024

Acceptance Date

March 25, 2025

Published in Issue

Year 2025 Volume: 18 Number: 4

APA
Kahvecioğlu, C., Ast, M. C., & Sağlık, A. (2025). Text to Image in Landscape Architecture: Artificial Intelligence Approaches. Kent Akademisi, 18(4), 1824-1844. https://doi.org/10.35674/kent.1588484
AMA
1.Kahvecioğlu C, Ast MC, Sağlık A. Text to Image in Landscape Architecture: Artificial Intelligence Approaches. Urban Academy. 2025;18(4):1824-1844. doi:10.35674/kent.1588484
Chicago
Kahvecioğlu, Ceren, Mahmut Can Ast, and Alper Sağlık. 2025. “Text to Image in Landscape Architecture: Artificial Intelligence Approaches”. Kent Akademisi 18 (4): 1824-44. https://doi.org/10.35674/kent.1588484.
EndNote
Kahvecioğlu C, Ast MC, Sağlık A (July 1, 2025) Text to Image in Landscape Architecture: Artificial Intelligence Approaches. Kent Akademisi 18 4 1824–1844.
IEEE
[1]C. Kahvecioğlu, M. C. Ast, and A. Sağlık, “Text to Image in Landscape Architecture: Artificial Intelligence Approaches”, Urban Academy, vol. 18, no. 4, pp. 1824–1844, July 2025, doi: 10.35674/kent.1588484.
ISNAD
Kahvecioğlu, Ceren - Ast, Mahmut Can - Sağlık, Alper. “Text to Image in Landscape Architecture: Artificial Intelligence Approaches”. Kent Akademisi 18/4 (July 1, 2025): 1824-1844. https://doi.org/10.35674/kent.1588484.
JAMA
1.Kahvecioğlu C, Ast MC, Sağlık A. Text to Image in Landscape Architecture: Artificial Intelligence Approaches. Urban Academy. 2025;18:1824–1844.
MLA
Kahvecioğlu, Ceren, et al. “Text to Image in Landscape Architecture: Artificial Intelligence Approaches”. Kent Akademisi, vol. 18, no. 4, July 2025, pp. 1824-4, doi:10.35674/kent.1588484.
Vancouver
1.Ceren Kahvecioğlu, Mahmut Can Ast, Alper Sağlık. Text to Image in Landscape Architecture: Artificial Intelligence Approaches. Urban Academy. 2025 Jul. 1;18(4):1824-4. doi:10.35674/kent.1588484

Cited By

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