LAUSR

Since virtual geographic environments (VGEs) were unofficially proposed for the first time at a conference in 1998, nearly two decades have passed. During these years, VGE has experienced several stages of evolution (Chen, Lin, and Lu 2017), and its definition has been modified over the course of its evolution (see Lin and Gong 2001; Lin and Zhu 2005; Gong, Zhou, and Zhang 2010; Lu 2011; Lin, Chen, and Lu 2013; Lin et al. 2013; Chen et al. 2017). Currently, the term VGE can be described as a kind of 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 multi-channel human–computer interactions (HCIs), distributed geographic modelling and simulations, and network geo-collaborations. Generally, according to the categories of geographic processes and phenomena that are embraced in VGEs (Lin et al. 2015), there are mainly three typical types of VGEs: similar and enhanced contemporary geographic environments, reproduced and recovered historical geographic environments, and predicted and planned future geographic environments. This latest definition provides a clearer description of VGEs; in particular, it indicates that the main body of VGEs is geographic environments, not just virtual environments. Recently, there has been an appearance in the revival of VR, in addition, the rising of Augmented Reality (AR) and Mixed Reality (MR), will cause VGEs to make great developmental progress. In our opinion, the enhanced VR/AR/MR can obviously benefit users by providing virtual or virtual–real mixed environments for a more natural and realistic perception and experience; however, virtual environments can be essential digital geographic environments only after geographic laws, rules and knowledges are integrated. From the perspective of geographers, a geographic environment is not just a spatial space, it is more; geographic environments mainly refer to the surfaces on which human societies exist and develop, and they are composed of various kinds of syntheses (including both natural and social factors). To better reflect geographic environments, by accepting static spatial variations and patterns, dynamic evolutionary processes and mutual interactions are all key objects that need more attention. VR/AR/MR are mostly employed to build spaces (either virtual or mixed) with rich geometrical and physical attributions, but geographic processes, phenomena and interactive mechanisms at different scales can only be provided from geographic aspects. This is the very distinction between VGEs and other purely VR/AR/MR technology-based environments. Therefore, understanding the integration of geography into environmental construction is the key to building VGEs. Following the appropriate architecture we proposed in 2013 (Lin, Chen, and Lu 2013a), the four sub-environments, i.e. data environments, modelling and simulation environments, expression environments (former interactive environments), and collaborative and interactive environments (former collaborative environments), should be designed together to fill the gaps. Detailed information can be acquired from previous studies (see Lin, Chen, and Lu 2013a, 2013b; Chen et al. 2017), and cases related to technology application on sub-environments can also be found (e.g. Chen et al. 2012, 2013; Mekni 2012; Xu et al. 2013; Zhang, Lin, and Min 2014, 2015; Liang, Gong, and Li 2015; Rybansky et al. 2015; Torrens 2015a, 2015b; Zhu et al. 2015; Yin et al. 2017). However, it is still worth emphasizing that: Data environments are the basic foundation for the development of VGEs. Since our geographers believe that geographic information contains context richer than spatiotemporal information,