Synthetic geospatial data and fake geography: A case study on the implications of AI-derived data in a data-intensive society

This paper presents a case study that aims to analyze and compare original and synthetic geospatial data at the intra-urban scale. The goal is to explore the potential implications of the spread of synthetic data in scenarios where geospatial data are essential for decoding socio-spatial changes and where Geo-visualization is pivotal for spatial decision support. The methodology is based on a) the production of a synthetic dataset and b) the evaluation of the spatial similarity with the original one. Specifically, we employ a synthetic data provider, namely Mostly.AI, alongside geospatial data related to Airbnb listings in Florence, Italy. Results show which criticalities are linked to AI-derived data compared to the original ones, highlighting crucial spatial similarities and dissimilarities. Finally, the work critically discusses the broader societal implications of the widespread online synthetic data platforms, exploring the impacts of such a technological (re)evolution in a data-intensive society.

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Publication Details

Journal
Digital Geography and Society
Published
2024-12-04
DOI
https://doi.org/10.1016/j.diggeo.2024.100108
Citations
7
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
4.78
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article

Synthetic geospatial data and fake geography: A case study on the implications of AI-derived data in a data-intensive society

Antonello Romano
7 citations
Digital Geography and Society
Human Mobility and Location-Based Analysis
4.78
article

Synthetic geospatial data and fake geography: A case study on the implications of AI-derived data in a data-intensive society

Antonello Romano
article en
7 citations

Abstract

This paper presents a case study that aims to analyze and compare original and synthetic geospatial data at the intra-urban scale. The goal is to explore the potential implications of the spread of synthetic data in scenarios where geospatial data are essential for decoding socio-spatial changes and where Geo-visualization is pivotal for spatial decision support. The methodology is based on a) the production of a synthetic dataset and b) the evaluation of the spatial similarity with the original one. Specifically, we employ a synthetic data provider, namely Mostly.AI, alongside geospatial data related to Airbnb listings in Florence, Italy. Results show which criticalities are linked to AI-derived data compared to the original ones, highlighting crucial spatial similarities and dissimilarities. Finally, the work critically discusses the broader societal implications of the widespread online synthetic data platforms, exploring the impacts of such a technological (re)evolution in a data-intensive society.

Digital Geography and SocietyVol. 8
University of Pisa (IT)
Climate action
Openalex Percentile: Top 6%
Human Mobility and Location-Based Analysis
4.78
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