| 摘要: |
| 在城市发展的转型革新、大数据的广泛应用和人工智能的技术突破三大背景下，从理论基础、数据来源、技术方法三方面出发，构建城市意象理论、大数据、深度学习相结合的城市意象认知新方法，从意象结构、意象类型和意象评价3个维度深度刻画城市意象。并借助新浪微博数据，利用深度学习对重庆主城区的城市意象认知进行实证研究，总结出重庆城市意象存在自然山水失落、人文要素缺失、意象结构有待优化等问题，验证了该认知方法的适用性与科学性。 |
| 关键词: 风景园林 城市意象 大数据 深度学习 微博 重庆 |
| DOI： |
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| 基金项目: |
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| The Innovation of City Image Cognitive Method Based on Deep Learning—A Case Study of Chongqing Main District |
| CAO Yuehao,YANG Peifeng,LONG Ying |
| Abstract: |
| Under the background of wide application of big data, technological breakthrough of artificial intelligence and transformation and innovation of urban planning, this paper, based on the three aspects of theoretical basis, data sources, and technical methods, aims to build a new cognitive method of city image based on the combination of city image theory, big data and deep learning, which depicts the city image in depth from the three dimensions of structure, type and evaluation. This paper makes an empirical research on the city image cognition of Chongqing by using Weibo data, Microsoft computer vision and Boson NLP platform, and concludes some problems in the city image of Chongqing, such as the loss of natural landscape, the lack of human elements and the needs to be optimized of the city image structure, which prove the validity and scientificity of the method. |
| Key words: : landscape architecture city image big data deep learning weibo Chongqing |
