基于轨迹时空图像的混合城市功能自监督检测方法

IF 7.1 1区 地球科学 Q1 ENVIRONMENTAL STUDIES Computers Environment and Urban Systems Pub Date : 2024-04-05 DOI:10.1016/j.compenvurbsys.2024.102113
Zhixing Chen , Luliang Tang , Xiaogang Guo , Guizhou Zheng
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引用次数: 0

摘要

城市功能检测在城市复杂系统识别和智慧城市建设中发挥着重要作用。从人类活动中获取的位置大数据与城市功能相辅相成,可为人类流动模式提供有价值的洞察。然而,随着城市功能的高度混合,现有的特征表示结构难以明确描绘潜在的人类活动特征,从而限制了以监督方式检测混合城市功能的适用性。为了缩小这一差距,本研究将潜在人类活动特征类比为图像的形状、纹理和颜色语义,并引入对比学习框架,提取基于图像的人群流动特征,用于检测混合城市功能。首先,通过将人类活动特征转化为图像语义,提出了一种称为轨迹时态图像(TTI)的新型特征表示结构,以明确表示人类活动特征。其次,采用视觉转换器(ViT)模型,以自我监督的方式提取基于图像的语义。最后,基于城市动力学,建立了表示混合城市函数的数学模型,并利用模糊集理论实现了混合城市函数的分解。利用中国三个城市的出租车轨迹数据进行了案例研究。实验结果表明,我们提出的方法具有很高的辨别能力,尤其是在活动强度较弱的地区,并揭示了混合指数与行程距离之间的关系。所提出的方法有望为理解城市复杂系统奠定坚实的科学基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A self-supervised detection method for mixed urban functions based on trajectory temporal image

Urban function detection plays a significant role in urban complex system recognition and smart city construction. The location big data obtained from human activities, which is cohesive with urban functions, provides valuable insights into human mobility patterns. However, as urban functions become highly mixed, existing feature representation structures struggle to explicitly depict the latent human activity features, limiting their applicability for detecting mixed urban functions in a supervised manner. To close the gap, this study analogizes the latent human activity features to the shape, texture, and color semantics of images, with a contrastive learning framework being introduced to extract image-based crowd mobility features for detecting mixed urban functions. Firstly, by translating human activity features into image semantics, a novel feature representation structure termed the Trajectory Temporal Image (TTI) is proposed to explicitly represent human activity features. Secondly, the Vision Transformer (ViT) model is employed to extract image-based semantics in a self-supervised manner. Lastly, based on urban dynamics, a mathematical model is developed to represent mixed urban functions, and the decomposition of mixed urban functions is achieved using the theory of fuzzy sets. A case study is conducted using taxi trajectory data in three cities in China. Experimental results indicate the high discriminability of our proposed method, especially in areas with weak activity intensity, and reveal the relationship between the mixture index and the trip distance. The proposed method is promising to establish a solid scientific foundation for comprehending the urban complex system.

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来源期刊
CiteScore
13.30
自引率
7.40%
发文量
111
审稿时长
32 days
期刊介绍: Computers, Environment and Urban Systemsis an interdisciplinary journal publishing cutting-edge and innovative computer-based research on environmental and urban systems, that privileges the geospatial perspective. The journal welcomes original high quality scholarship of a theoretical, applied or technological nature, and provides a stimulating presentation of perspectives, research developments, overviews of important new technologies and uses of major computational, information-based, and visualization innovations. Applied and theoretical contributions demonstrate the scope of computer-based analysis fostering a better understanding of environmental and urban systems, their spatial scope and their dynamics.
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