Artificial intelligence studies in cartography: a review and synthesis of methods, applications, and ethics

Kang, Yuhao; Gao, Song; Roth, Robert E.

doi:10.1080/15230406.2023.2295943

Cited by 11 publications

(4 citation statements)

References 201 publications

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“…As a consequence, the use of AI is unavoidable for most firms that are required to keep up to date with new technology (Bond et al, 2024). AI is a form of digital technology that is playing a key role in transforming international business practices including production and process management (Kang et al, 2024). Mariani and Borghi (2023, p. 3) states that "the periphrasis 'artificial intelligence' was coined in 1956 on the occasion of the Dartmouth Summer Research Project on Artificial Intelligence (DSRAI) hosted at Dartmouth College (U.S.A.) by scientists Marvin Minsky and John McCarthy".…”

Section: Artificial Intelligence and Digital Technologymentioning

confidence: 99%

Art galleries usage of artificial intelligence

Ratten

2024

IJSSP

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PurposeRecently there has been a surge in interest about the use of artificial intelligence in organisations with art galleries introducing new technological innovations that coincide with the digitalisation revolution. Virtual and immersive environments that are supported by social media and digital platforms are significantly changing customer experiences at art galleries. This is internationalising and making art gallery experiences more accessible thereby fostering the competitive advantage of art galleries.Design/methodology/approachArt gallery customers, stakeholders and managers are appreciating the use of artificial intelligence with resulting higher satisfaction rates. Building on competency and transformational entrepreneurship theory international art gallery managers were interviewed to understand the role of artificial intelligence in their organisations and the impact of internationalisation.FindingsThe data analysis revealed that the internationalisation of art galleries enabled artificial intelligence to transform in person and online visitor experience, work and marketing, and future art gallery development ideas. Results show that artificial intelligence is opening up new transformations derived from entrepreneurial behaviours.Originality/valueKey managerial implications are that art gallery managers need to utilise their international networks in order to learn about artificial intelligence and other new technological innovation. Theoretical implications are that existing theory can be adapted to an art gallery and artificial intelligence context. Limitations and future research suggestions focus on the need to focus more on art galleries as cultural entities that are more likely to utilise new technology innovation such as artificial intelligence.

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Section: Artificial Intelligence and Digital Technologymentioning

confidence: 99%

Art galleries usage of artificial intelligence

Ratten

2024

IJSSP

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“…Currently, a large number of raster maps are available on the internet because of advancements in computer science and internet technology; they are derived from scanned historical maps, contemporary atlases, vector-to-raster maps with original vector data missing, hand-drawn maps, etc. The geographic information locked in raster maps is crucial for researchers to understand long-term development in an area without manual on-site data acquisition [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…Map interpretation is important for the development of geospatial intelligence [12]. Administrative regions represent fundamental geographic information for depicting locations where current research is taking place [4] and providing a framework for public administration [9].…”

Section: Introductionmentioning

confidence: 99%

Integration of Spatial and Co-Existence Relationships to Improve Administrative Region Target Detection in Map Images

Du,

Ren,

Wang

et al. 2024

IJGI

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Administrative regions are fundamental geographic elements on maps, thus making their detection in map images crucial to enhancing intelligent map interpretation. However, existing methods in this field primarily depend on the texture features within the images and do not account for the influence of spatial and co-existence relationships among different targets. In this study, taking the administrative regions of the Chinese Mainland, Taiwan, Tibet, and Henan as test targets, we employed the spatial and co-existence relationships of pairs of targets to improve target detection performance. Firstly, these four regions were detected using a simple Single-Target Cascading detection model based on RetinaNet. Subsequently, the detection results were adjusted with the spatial and co-existence relationships of each pair of targets. The adjusted outcomes demonstrate a significant increase in target detection accuracy, as well as precision (from 0.62 to 0.96) and F1 score (from 0.76 to 0.88), for the Chinese Mainland target. This study contributes to the advancement of intelligent map interpretation.

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“…GeoAI is the use of AI and machine learning in geography [30] to develop approaches related to spatiotemporal problems [31]. AI could substantially support the production of personalized maps [32,33]. User data collected utilizing eye tracking or other user response methods (e.g., mouse tracking [34]), can be used as input for on-the-fly map design processes.…”

Section: Introductionmentioning

confidence: 99%

OnMapGaze and GraphGazeD: A Gaze Dataset and a Graph-Based Metric for Modeling Visual Perception Differences in Cartographic Backgrounds Used in Online Map Services

Liaskos,

Krassanakis

2024

MTI

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In the present study, a new eye-tracking dataset (OnMapGaze) and a graph-based metric (GraphGazeD) for modeling visual perception differences are introduced. The dataset includes both experimental and analyzed gaze data collected during the observation of different cartographic backgrounds used in five online map services, including Google Maps, Wikimedia, Bing Maps, ESRI, and OSM, at three different zoom levels (12z, 14z, and 16z). The computation of the new metric is based on the utilization of aggregated gaze behavior data. Our dataset aims to serve as an objective ground truth for feeding artificial intelligence (AI) algorithms and developing computational models for predicting visual behavior during map reading. Both the OnMapGaze dataset and the source code for computing the GraphGazeD metric are freely distributed to the scientific community.

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Artificial intelligence studies in cartography: a review and synthesis of methods, applications, and ethics

Cited by 11 publications

References 201 publications

Art galleries usage of artificial intelligence

Art galleries usage of artificial intelligence

Integration of Spatial and Co-Existence Relationships to Improve Administrative Region Target Detection in Map Images

OnMapGaze and GraphGazeD: A Gaze Dataset and a Graph-Based Metric for Modeling Visual Perception Differences in Cartographic Backgrounds Used in Online Map Services

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