| 交通大数据在人文与经济地理学的应用及学科影响 |
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| 引用本文： | 黄洁,王姣娥.交通大数据在人文与经济地理学的应用及学科影响[J].地球信息科学,2020,22(6):1180-1188. |
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| 作者姓名： | 黄洁 王姣娥 |
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| 作者单位： | 1. 中国科学院地理科学与资源研究所 中国科学院区域可持续发展分析与模拟重点实验室,北京 1001012. 中国科学院大学资源与环境学院,北京 100049 |
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| 基金项目： | 中国科学院战略性先导科技专项(A类)(XDA19040402);国家自然科学基金项目(41701132) |
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| 摘 要： | 交通大数据能够反映人类社会经济活动产生的位移与时空轨迹,不仅能够满足学者们在微观尺度更深入、更精细的研究粒度要求,而且能够为宏观尺度的研究提供广范围、多视角的连续性观测,其研究与发展为人文与经济地理学带来了新思路和新技术。本文以交通大数据的研究前沿为基础,梳理了区位论、时空行为、复杂网络、流空间等理论研究的发展方向,勾勒了"大数据时代"背景下人文与经济地理学的研究框架体系,探讨了新旧技术方法融合的可能性,并讨论了对各个分支学科相关研究的影响。接着,本文总结了交通大数据在人文与经济地理学的主要应用方向与趋势,主要包括出行即服务的交通规划理论与方法,"人工智能+大数据"的城市管理科学,大尺度交通流迁移的模拟,以及"流空间"与"场所空间"的多维度研究等。最后,本文指出了交通大数据应用在获取难度和数据有偏性等方面值得注意的问题并进行了展望。
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| 关 键 词： | 大数据 交通 个人出行 信息技术 地理学 学科创新 |
| 收稿时间： | 2019-10-25 |
Applications and Influence of Transport Big Data in Human and Economic Geography |
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| HUANG Jie,WANG Jiaoe.Applications and Influence of Transport Big Data in Human and Economic Geography[J].Geo-information Science,2020,22(6):1180-1188. |
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| Authors: | HUANG Jie WANG Jiaoe |
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| Institution: | 1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Transport big data can reflect movement and trajectories of human socio-economic activities, and facilitate studies in a wide range of areas using high-resolution data. Various types of continuous observations from different perspectives can provide new ideas and promote the technological development of human and economic geography. Based on the frontier of transport studies, this paper reviewed the development of location theory, time and space behavior, complex network, and space of flow. Also, this paper outlined a research framework of human and economic geography in the era of big data, discussed the possibilities of combining traditional methods and new technologies, and summarized influences of related branches. Then we proposed the major direction and tendency of applying transport big data, including transport planning with 'Mobility as a Service', urban management with artificial intelligence, simulation of traffic flow migration at a large scale, and investigationof space of flow and space at multiple scales, etc. Finally, this paper pointed out emerging issues in the application such as data access and data bias. |
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| Keywords: | big data transport individual travel information technology geography disciplinary innovation |
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