E3S Web Conf.
Volume 236, 20213rd International Conference on Energy Resources and Sustainable Development (ICERSD 2020)
|Number of page(s)||6|
|Section||Sustainable Development and Prevention of Urban Environmental Pollution|
|Published online||09 February 2021|
Construction of Characteristic Town Brand Color Systems: Color Extraction Based on Regional Landscape Architecture
Art School, Jiangsu University, Zhenjiang, Jiangsu, 202013, China
The brand image design of characteristic towns already becomes the way to improve awareness and promote propaganda in many characteristic towns. However, during the brand color system construction of characteristic towns, the differences in natural geography and cultural landscape have resulted in universal differentiation of characteristic towns, but the brand color constructions are very similar and lack scientific basis or differences, and even deviate from the original intention of town brand building. Given the difficulty in the brand color system development of characteristic towns, we proposed a strategy to build the characteristic town brand color system according to the color extraction from regional landscape buildings. With the characteristic Xiaolan Town in Zhongshan City of Guangdong province as example, the features of natural landscape plants and architecture color design were extracted on basis of the comprehensive regional landscapes. The color library for color design was acquired through data analysis, and the colors of historical landscape buildings were integrated with the colors of modern science and technology elements. With the introduction of building graphs, the deep connection between color design and brand visual image was enhanced. This design strategy offers some scientific values and theoretical guidance for exploring the brand color design systems of characteristic towns and for guiding the innovative strategies of designers.
© The Authors, published by EDP Sciences 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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