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Volume 13
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10.3390/land13020254
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Article

Enhancing Urban Landscape Design: A GAN-Based Approach for Rapid Color Rendering of Park Sketches

by
Ran Chen
1,
Jing Zhao
1,*,
Xueqi Yao
1,
Yueheng He
1,
Yuting Li
1,
Zeke Lian
2,
Zhengqi Han
1,
Xingjian Yi
1 and
Haoran Li
3
1
School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
2
Ningbo City College of Vocational Technology, Ningbo 315100, China
3
China United Network Communications Group Co., Beijing 100031, China
*
Author to whom correspondence should be addressed.
Land 2024, 13(2), 254; https://doi.org/10.3390/land13020254
Submission received: 13 December 2023 / Revised: 9 February 2024 / Accepted: 10 February 2024 / Published: 18 February 2024
(This article belongs to the Special Issue Landscape Design, Evaluation and Management Created by Novel Technologies)
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Abstract

In urban ecological development, the effective planning and design of living spaces are crucial. Traditional color plan rendering methods, mainly using generative adversarial networks (GANs), rely heavily on edge extraction. This often leads to the loss of important details from hand-drawn drafts, significantly affecting the portrayal of the designer’s key concepts. This issue is especially critical in complex park planning. To address this, our study introduces a system based on conditional GANs. This system rapidly converts black-and-white park sketches into comprehensive color designs. We also employ a data augmentation strategy to enhance the quality of the output. The research reveals: (1) Our model efficiently produces designs suitable for industrial applications. (2) The GAN-based data augmentation improves the data volume, leading to enhanced rendering effects. (3) Our unique approach of direct rendering from sketches offers a novel method in urban planning and design. This study aims to enhance the rendering aspect of an intelligent workflow for landscape design. More efficient rendering techniques will reduce the iteration time of early design solutions and promote the iterative speed of designers’ thinking, thus improving the speed and efficiency of the whole design process.
Keywords: hand-drawn sketch; image color rendering; generative adversarial networks; data augmentation; landscape design hand-drawn sketch; image color rendering; generative adversarial networks; data augmentation; landscape design

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MDPI and ACS Style

Chen, R.; Zhao, J.; Yao, X.; He, Y.; Li, Y.; Lian, Z.; Han, Z.; Yi, X.; Li, H. Enhancing Urban Landscape Design: A GAN-Based Approach for Rapid Color Rendering of Park Sketches. Land 2024, 13, 254. https://doi.org/10.3390/land13020254

AMA Style

Chen R, Zhao J, Yao X, He Y, Li Y, Lian Z, Han Z, Yi X, Li H. Enhancing Urban Landscape Design: A GAN-Based Approach for Rapid Color Rendering of Park Sketches. Land. 2024; 13(2):254. https://doi.org/10.3390/land13020254

Chicago/Turabian Style

Chen, Ran, Jing Zhao, Xueqi Yao, Yueheng He, Yuting Li, Zeke Lian, Zhengqi Han, Xingjian Yi, and Haoran Li. 2024. "Enhancing Urban Landscape Design: A GAN-Based Approach for Rapid Color Rendering of Park Sketches" Land 13, no. 2: 254. https://doi.org/10.3390/land13020254

APA Style

Chen, R., Zhao, J., Yao, X., He, Y., Li, Y., Lian, Z., Han, Z., Yi, X., & Li, H. (2024). Enhancing Urban Landscape Design: A GAN-Based Approach for Rapid Color Rendering of Park Sketches. Land, 13(2), 254. https://doi.org/10.3390/land13020254

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