人群动态的观测理论及其未来发展思考

doi:10.12082/dqxxkx.2021.200787

摘要/Abstract

摘要：

在“新冠”肺炎疫情发展过程中,人群动态的观测理论研究与应用受到了国内外许多研究人员和民众的重点关注,特别是公共卫生学、临床医学、地理学、公共管理学等多学科交叉,探索科学的疫情动态监测、精准防控、准确预测与有效应对等方面的理论与方法。本文首先系统介绍人群动态的观测理论研究背景和意义,概括地描述其核心的3个问题（观测其如何变、分析其为何变、控制其如何变）,从信息地理学、测绘学等领域角度阐述人群动态的观测理论研究意义及其学科价值。接着,围绕人群动态的观测与时空应用,本文阐述地理时空大数据背景下人群动态的关键观测理论框架（如基础时空理论、时空定量与综合观测理论、时空过程优化理论等）,及其所存在的瓶颈问题和发展需求。然后,结合未来理论研究与关注变化,阐述了4个典型的人群动态观测理论趋势变化,包括：数字化社会治理与公共安全/卫生应急等需求驱动下的精细化观测、公共利益至上与个人保护最大化兼顾下的差异化观测、对人观测与对地观测的集成化观测理论发展、高阶需求层次管控与服务的人群动态观测理论突破。最后,本文强调在多学科交叉背景下,指出重点发展人群大数据感知、多空间精细化观测、人地系统化建模等方面的基础理论与方法,实现差异化、集成化、层次化的对人观测,系统支撑面向地学的研究与时空应用,科学支撑不可逆的管理、控制、服务等社会治理现实应用决策。该方面理论研究,将对“新城镇化”、“美丽中国”、“人工智能”、“新基建”等国家战略中城市和区域的绿色、高效、智慧与可持续发展等都有重要支撑作用。

关键词: 人群动态观测, 城市动态感知, 时空过程, 时空建模, 时空服务, 数字化治理, 公共安全, 公共卫生

Abstract:

During the development of COVID-19 virus's global epidemic, the fundamental research and various applications of crowd dynamics-oriented observation theories have attracted much attention from many researchers and people all over the world within some related disciplines, such as public health, clinical medicine, geography, public management, etc. Researchers conducted many interdisciplinary explorations in theories and methods of monitoring epidemic dynamics scientifically, preventing and controlling spatial transmission precisely, predicting accurately, and responding effectively. However, no crowd dynamics-oriented observation theories have been proposed in literature so far. This paper revisits the concept and introduces a theory framework of crowd dynamics-oriented observation, which tries to include the core theories of observation from geospatial big data and to support diverse potential developments. Firstly, this article introduces the research background of crowd dynamics-oriented observation, and then summarizes its three core questions (how to observe its change, how to analyze its change, and how to control its change). From the inter-discipline view of geographic information science, surveying and mapping science, this paper explains the research significance and disciplinary value of crowd dynamics-oriented observation theories. Secondly, this paper introduces a framework of crowd dynamics-oriented observation and its spatiotemporal application, and then elaborates on the bottleneck problems of the key observation theories of crowd dynamics, such as fundamental space-time framework theory, space-time quantification and comprehensive observation theory, spatiotemporal process optimization theory, etc. Thirdly, this paper preliminarily introduces some changes of crowd dynamics-oriented observation theories, for example, refined observation driven by the application needs of digital society governance and public safety/health emergency, personal privacy protection and personalized observations by balancing the public interest and personal privacies, the development of integrated observation theories for human-oriented observation and earth-oriented observation, and the theory of crowd dynamics-oriented observation for high-level management and service. Finally, this article points out the potential directions of crowd dynamics-oriented observation theory and methods, such as, the development of big data-driven crowd perception, multi-space refined crowd dynamics observation, and human-land systematical interaction modeling, so as to realize some differentiated, integrated, and hierarchical crowd dynamics-oriented observations. All potential theories are helpful to the scientific decision-making of public management and public service. The crowd dynamics-oriented observation theory should focus on the fundamental research questions related to studying, analyzing, and servicing human beings, which has become a research frontier in geospatial information science, and could play very important roles in supporting national development strategies, such as "New urbanization", "beautiful China", "artificial intelligence", and "new infrastructure", so as to contribute to a green, efficient, smart, and sustainable regional and urban development.

Key words: crowd dynamics observation, urban dynamics sensing, spatiotemporal progress, spatiotemporal modelling, space-time service, digital governance, public security, public health

方志祥. 人群动态的观测理论及其未来发展思考[J]. 地球信息科学学报, 2021, 23(9): 1527-1536.DOI:10.12082/dqxxkx.2021.200787

FANG Zhixiang. The Theory Prospect of Crowd Dynamics-oriented Observation[J]. Journal of Geo-information Science, 2021, 23(9): 1527-1536.DOI:10.12082/dqxxkx.2021.200787

图/表 3

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