In This Article Expand or collapse the "in this article" section GIScience of Human Dynamics

  • Introduction
  • General Overviews
  • Reference Resources: Conferences/Tools
  • Reference Resources: Research Institutions / Research Groups
  • Journals
  • Urban Dynamics with Cellular Automata Approach
  • Complex Systems and Other Computational Approaches
  • Effects of Technological Advances and Data Science
  • Volunteered Geographic Information and Crowdsourcing Geographic Knowledge
  • Space-Time GIS and Time Geography
  • Spatiotemporal Human Dynamics Research with Time-Geographic Approach
  • Future Prospects and Challenges of Human Dynamics Research with GIScience

Geography GIScience of Human Dynamics
by
Shih-Lung Shaw
  • LAST REVIEWED: 23 March 2022
  • LAST MODIFIED: 23 March 2022
  • DOI: 10.1093/obo/9780199874002-0239

Introduction

Human dynamics, which encompasses all forms of human activities and interactions, plays critical roles in the economic, social, cultural, and political systems of human societies around the world. Understanding human dynamics therefore is an important research topic that has been pursued in many disciplines. Human dynamics evolves with the changing environments, cultures, and technologies over time. With the rapid technological advances since the late 20th century, we have observed increasing human activities and interactions taking place in a hybrid physical-virtual world, such as online shopping in virtual space coupled with deliveries of the purchased items in physical space. Although geographic information systems (GIS) have been used extensively to study human activity patterns such as urban growth and traffic flows, there remain many challenges of addressing both the “human” aspect and the “dynamic” nature of human dynamics in a GIS environment. First of all, human dynamics research must consider space, time, and humans at the same time. In spite of significant progress in the development of space-time GIS, current GIS and geographic information science (GIScience) falls short of properly considering humans in a GIS environment. There is an urgent need of developing a theoretical framework of integrating space, time, and humans in GIScience. Second, human dynamics can be studied at a disaggregate level or at an aggregate level that requires different conceptualizations, models, and methods to understand individual versus group behaviors. Next, locations in physical space, which are frequently represented as coordinates in an absolute space, have been the cornerstone of conventional GIS. As human activities and interactions in virtual space (e.g., e-commerce, e-government, online social networks) have become common practices in our daily lives, the conventional approach of using coordinates in absolute space to build GIS databases is insufficient to support various kinds of human dynamics. For example, the concept of relational space that emphasizes connections rather than locations can be a useful way of studying online social networks. Finally, we need to keep in mind that a key reason of pursuing human dynamics research is to gain better understanding of human behaviors, such that we can improve the quality of life through better designs of the built environments and services to meet various human needs. This article presents relevant research work related to these challenges of GIScience of human dynamics research.

General Overviews

As a transdisciplinary research topic, human dynamics research has been pursued in various disciplines with different approaches. For example, Seagal and Horne 1997 is a book titled Human Dynamics that presents a framework for understanding people and their dynamics in organizational systems. The author of Bregler 1997 develops a method of learning and recognizing human dynamics in video sequences. They all fall within the scope of human dynamics research in a broad sense. Forrester 1969 is a pioneering book titled Urban Dynamics that uses a computer simulation approach to study the structure, growth, stagnation, and revival of urban areas. This computer simulation approach has been taken in many GIS studies to investigate urban development and other dynamic spatial patterns. Batty 2005 offers a review of using cellular automata (CA) and agent-based models for simulation of urban systems. Most research of urban dynamics placed an emphasis on the aggregate outcomes rather than on disaggregate human dynamics at the individual level. As Hey, et al. 2009 discusses the emerging fourth paradigm of data-intensive science enabled by modern technologies, there has been a surge of human dynamics research based on various kinds of big data collected at the individual level in a space-time context. This rise of human dynamics research presents new challenges to GIS and GIScience with respect to representation, analysis, and visualization of space, time, and human dynamics in an integrated environment. Time geography, presented in Hägerstrand 1970, and space-time GIS, discussed in Goodchild 2013, have become useful approaches of studying individual human dynamics. Furthermore, conventional GIS, with a focus on coordinates in absolute space, is limited in gaining insights into various aspects of human dynamics. For example, Bergman and O’Sullivan 2018 argues that relational conceptions of space that are common in human geography could fundamentally alter some basic GIS and GIScience concepts. Shaw and Sui 2020 further presents a human-centered, space-place (splatial) GIScience framework that covers multiple concepts of space and place to better support human dynamics research.

  • Batty, Michael. “Agents, Cells, and Cities: New Representational Models for Simulating Multiscale Urban Dynamics.” Environment and Planning A: Economy and Space 37.8 (2005): 1373–1394.

    DOI: 10.1068/a3784

    This paper provides a review of urban system simulations using cellular automata and agent-based models.

  • Bergman, Luke, and David O’Sullivan. “Reimagining GIScience for Relational Spaces.” Canadian Geographer 62.1 (2018): 7–14.

    DOI: 10.1111/cag.12405

    This paper presents an approach of reformulating the computational approach to the region for relational space, such that regions emerge not through proximity or similarity in an absolute space but according to their similarities in relations.

  • Bregler, Christoph. “Learning and Recognizing Human Dynamics in Video Sequences.” In Proceedings: 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 17–19, 1997, San Juan, Puerto Rico. Edited by IEEE Computer Society, 568–574. Los Alamitos, CA: IEEE Computer Society Press, 1997.

    This paper develops an approach to learning and recognizing human movements in video sequences of an unconstrained environment. It starts with low-level primitives of coherent motion and progresses to mid-level categories of simple movements. High-level complex gestures then can be represented as successive phases of simple movements.

  • Forrester, Jay W. Urban Dynamics. Cambridge, MA: MIT Press, 1969.

    This book takes a system dynamics approach to simulate urban dynamics, which is among three well-known books published by Jay Forrester (Industrial Dynamics, 1961; Urban Dynamics, 1969; and World Dynamics, 1971).

  • Goodchild, Michael F. “Prospects for a Space–Time GIS.” Annals of the Association of American Geographers 103.5 (2013): 1072–1077.

    DOI: 10.1080/00045608.2013.792175

    This paper presents seven examples of distinct data types and scientific questions to discuss the prospects and challenges of developing space-time geographic information systems.

  • Hägerstrand, Torsten. “What about People in Regional Science?” Papers of the Regional Science Association 24.1 (1970): 7–21.

    DOI: 10.1111/j.1435-5597.1970.tb01464.x

    This is the most frequently cited paper of time geography as developed by Torsten Hägerstrand, which presents the basic concepts of time geography such as path, constraint, prism, bundle, and domain in a time-space context.

  • Hey, Tony, Stewart Tansley, and Kristin Tolle, eds. The Fourth Paradigm: Data-Intensive Scientific Discovery. Redmond, WA: Microsoft Research, 2009.

    This book is a collection of articles related to the fourth paradigm and data-intensive science proposed by Jim Gray.

  • Seagal, Sandra, and David Horne. Human Dynamics. Cambridge, MA: Pegasus Communications, 1997.

    This book discusses human dynamics in the context of organizational development. It takes a personality dynamics view to identify the fundamental structures and describes the processes and functions in organizational systems.

  • Shaw, Shih-Lung, and Daniel Sui. “Understanding the New Human Dynamics in Smart Spaces and Places: Towards a Splatial Framework.” Annals of the American Association of Geographers 110.2 (2020): 339–348.

    DOI: 10.1080/24694452.2019.1631145

    This paper presents a new human-centered, space-place (splatial) GIScience framework that covers the concepts of absolute space, relative space, relational space, and mental space, as well as the concepts of location, locale, place identity, and sense of place for human dynamics research.

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