Framework for Virtual Cognitive Experiment in Virtual Geographic Environments

Abstract

Virtual Geographic Environment Cognition is the attempt to understand the human cognition of surface features, geographic processes, and human behaviour, as well as their relationships in the real world. From the perspective of human cognition behaviour analysis and simulation, previous work in Virtual Geographic Environments (VGEs) has focused mostly on representing and simulating the real world to create an 'interpretive' virtual world and improve an individual's active cognition. In terms of reactive cognition, building a user 'evaluative' environment in a complex virtual experiment is a necessary yet challenging task. This paper discusses the outlook of VGEs and proposes a framework for virtual cognitive experiments. The framework not only employs immersive virtual environment technology to create a realistic virtual world but also involves a responsive mechanism to record the user's cognitive activities during the experiment. Based on the framework, this paper presents two potential implementation methods: first, training a deep learning model with several hundred thousand street view images scored by online volunteers, with further analysis of which visual factors produce a sense of safety for the individual, and second, creating an immersive virtual environment and Electroencephalogram (EEG)-based experimental paradigm to both record and analyse the brain activity of a user and explore what type of virtual environment is more suitable and comfortable. Finally, we present some preliminary findings based on the first method.

Classifying Street Spaces with Street View Images for a Spatial Indicator of Urban Functions

“…The advent of street view images from Google StreetView and similar online data services has opened the door of opportunities to remedy this disadvantage. A series of recent studies managed to extract streetscape features from SVIs and applied them in a range of applications, including the perception and quality of the urban environment [15,[17][18][19][20], street livability and walkability [21][22][23][24], environmental audit for human health and wellbeing [25][26][27][28][29], urban inequality and socioeconomic changes of neighborhoods [30][31][32][33][34], urban safety [35,36], and information retrieval for adjacent land uses [37]. Among these studies, many assume implicitly or explicitly that the extracted streetscape features, representing the physical appearance of streets, from SVIs can reflect place-related functions that serve human activities both on the street and those associated with the uses of buildings on the sides [23,30,[32][33][34]37].…”

Geospatial Information Visualization and Extended Reality Displays

“…A modern description of a VGE is a digital geographic environment "generated by computers and related technologies that users can use to experience and recognize complex geographic systems and further conduct comprehensive geographic analyses, through equipped functions, including multichannel human-computer interactions (HCIs), distributed geographic modeling and simulations, and network geo-collaborations" (Chen and Lin 2018, p. 329). Since their conception, VGEs have attracted considerable attention in the geographic information science research community over the last few decades (e.g., Goodchild 2009;Huang et al 2018;Jia et al 2015;Konecny 2011;Liang et al 2015;Mekni 2010;Priestnall et al 2012;Rink et al 2018;Shen et al 2018;Torrens 2015;Zhang et al 2018;Zheng et al 2017). Much like the "digital twin" idea, and well-aligned with the Digital Earth concept, VGEs often aim to mirror realworld geographic environments in virtual ones.…”

Intelligent Interaction with Virtual Geographical Environments Based on Geographic Knowledge Graph

“…Virtual geographical environments (VGEs) were proposed in the late 1990s and have since been deeply studied with regards to visualization, geographic simulation, predictive analysis, knowledge sharing, collaborative modeling [1][2][3][4][5][6], and so on. With the development of artificial intelligence and big data, intelligent VGEs have to meet the new challenges of geographic knowledge engineering [7].…”