Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges

Chen, Min; Claramunt, Christophe; Çöltekin, Arzu; Liu, Xintao; Peng, Peng; Robinson, Anthony C.; Wang, Dajiang; Strobl, Josef; Wilson, John P.; Batty, Michael; Kwan, Mei‐Po; Lotfian, Maryam; Golay, François; Joost, Stéphane; Ingensand, Jens; Senousi, Ahmad M.; Cheng, Tao; Bandrova, Temenoujka; Konečný, Milan; Torrens, Paul M.; Klippel, Alexander; Li, Songnian; Zhang, Fengyuan; He, Li; Wang, Jinfeng; Ratti, Carlo; Kolditz, Olaf; Lin, Hui; Lv, Guonian

doi:10.1016/j.earscirev.2023.104438

Cited by 28 publications

(10 citation statements)

References 75 publications

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“…Rapid advancement of futurist GIScience shifts the human interaction from the geographic location to the cyberspace of topologic artificial intelligence and visual analytics as well [10]. The process of cyberspace includes spatiotemporal properties to embed in digital space, thus the human interconnections in real geographical space and not only virtual reality [for example 11,12,13,14].…”

Section: Methodsmentioning

confidence: 99%

Voronoi Structure of Space Integration with Applied Roundabout Network

El-Shazly

2024

Preprint

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Network objective of structuring space integration addresses topologic and geometric dimensions to be framed-out in holistic method. In this sense, the spatial network of multidiscipline voronoi convex-hull encapsulates the varied integral properties with their correlative exploration. In practice, conservational network of roundabout Cairo investigates its integral structure against decomposing. Resulted structural essence defines individual topologic versus plural geometric role at global integration per generator. The integrated topology cross-correlates control syntax with degree centrality at the local context, whereas the global structure of asymmetry complements betweenness dynamics of generators’ distributiveness. Meanwhile, geometrical network of gabriel-graph forms cyclic spaces of global integrity and correlated by voronoi nodes at equidistant meeting-point per cycle. Overlaid voronoi properties classify the layout into clustered generators of correlated interval integrity with functional cognition to infinity. Overview of voronoi network adopts the intangible space integration along its comprehensive framework of interrelated algorithms in a virtual reality of urbanism.

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Section: Methodsmentioning

confidence: 99%

Voronoi Structure of Space Integration with Applied Roundabout Network

El-Shazly

2024

Preprint

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“…ChatGPT, Bing Chat, and other similar techniques seem to be promising in solving such problems. In-depth model knowledge should be merged with these artificial intelligence (AI) tools to support better usage of geoscientific models (Chen et al, 2023;OpenAI, 2023;Rudolph et al, 2023). The GPT-like tools can also be promising in automatically generating knowledge contents for the model framework, for example, using ChatGPT reading an article introducing a model and then automatically offering the basic descriptions and a conceptual diagram explaining the model.…”

Section: Knowledge Applicationmentioning

confidence: 99%

Construction of an open knowledge framework for geoscientific models

Xu,

Yue,

Chen

et al. 2024

Transactions in GIS

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Geoscientific models have rapidly developed in recent decades as effective tools to understand the past, perceive the present, and predict the future. However, with the increasing number of models available, discovering suitable ones and applying them properly in problem‐solving situations has become more challenging. Existing materials describing geoscientific models (e.g., articles, manuals, handbooks, metadata documents, and web pages) are scattered and varied in structure and content. To help model users from different disciplinary backgrounds find, access, implement, and reuse models more conveniently, we propose an open knowledge framework for geoscientific models. The knowledge framework includes three levels: a resource level for indicating where to find a model, a connection level for indicating what materials are related to a model, and an application level for indicating how the model is applied. Through such a three‐level framework, model users can collaboratively provide descriptive information for a model, link different materials to a model (e.g., data, references, and tools), and contribute experiences regarding model application in practical cases (as reusable solutions). Thus, a web‐based community can be formed to facilitate the better use of geoscientific models. This article introduces the Open Geographic Modeling and Simulation System (OpenGMS) as the implementation of this open knowledge framework. Case studies are given to showcase the effectiveness and capability of the proposed framework.

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“…Such challenges are said to necessitate "innovative solutions" that "will only succeed through creative impulses, experiments, trying out innovative ideas, and making alternatives visible (Kagan, 2023) [77] in the face of emergence, unpredictability, and uncertainty. Chen et al (2023) [78] consider the challenges and opportunities associated with "geographical (physical) space" and "cyberspace" from the perspective of "data analytics and visualization, including extended AI capabilities and virtual reality representations", noting the potential "to improve sustainability and solve complex problems with geospatial applications (e.g., GeoAI, GeoVA (geovisual analytics))". While AI may be important to the development of smart cities, Rjab, Mellouli, and Corbett (2023) [79] provide a systematic review of the literature on the barriers to adoption in terms of a "novel mapping" pertaining to technology, environment, and organization followed by the development of a research agenda for moving forward.…”

Section: Cognitive Flexibility and Civic Spaces In Smart Cities And R...mentioning

confidence: 99%

Creativity and Innovation in Civic Spaces Supported by Cognitive Flexibility When Learning with AI Chatbots in Smart Cities

Chauncey,

McKenna

2024

Urban Science

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The purpose of this study is to advance conceptual understandings of the cognitive flexibility construct, in support of creativity and innovation in smart city civic spaces, employing the use of large language model artificial intelligence chatbots such as ChatGPT. Based on a review of the research and practice literature, this study formulates a conceptual framework for cognitive flexibility in support of creativity and innovation in AI environments, adaptable to smart cities. A research design is used that employs AI as a design material, in combination with a topical inquiry involving boundary setting and perspective taking, to co-pilot an exploration with ChatGPT-3.5/4. This study operationalizes the framework for applications to learning approaches, addressing flexibility and inclusivity in smart city spaces and regions. With the rapid evolving of chatbot technologies, ChatGPT-4 is used in the exploration of a speculative real-world urban example. This work is significant in that AI chatbots are explored for application in urban spaces involving creative ideation, iteration, engagement, and cognitive flexibility; future directions for exploration are identified pertaining to ethical and civil discourse in smart cities and learning cities, as well as the notion that AI chatbots and GPTs (generative pre-trained transformers) may become a zeitgeist for understanding and learning in smart cities.

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Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges

Cited by 28 publications

References 75 publications

Voronoi Structure of Space Integration with Applied Roundabout Network

Voronoi Structure of Space Integration with Applied Roundabout Network

Construction of an open knowledge framework for geoscientific models

Creativity and Innovation in Civic Spaces Supported by Cognitive Flexibility When Learning with AI Chatbots in Smart Cities

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