Deep fake geography? When geospatial data encounter Artificial Intelligence. Issue 4 (4th July 2021)

• Record Type: Journal Article
• Authors: Zhao, Bo; Zhang, Shaozeng; Xu, Chunxue; Sun, Yifan; Deng, Chengbin
• Is Part Of: Cartography and geographic information science. Volume 48:Issue 4(2021)
• Page Start: 338
• Page End: 352
• Publication Date: 2021-07-04
• Subjects: Artificial Intelligence -- geospatial data -- deep fake -- fake geography -- GeoAI -- fake satellite image -- Generative Adversarial Networks; Cartography -- Periodicals; Geographic information systems -- Periodicals; 526
• DOI: 10.1080/15230406.2021.1910075
• Languages: English
• ISSNs: 1523-0406

Abstract

ABSTRACT: The developing convergence of Artificial Intelligence and GIScience has raised a concern on the emergence of deep fake geography and its potentials in transforming human perception of the geographic world. Situating fake geography under the context of modern cartography and GIScience, this paper presents an empirical study to dissect the algorithmic mechanism of falsifying satellite images with non-existent landscape features. To demonstrate our pioneering attempt at deep fake detection, a robust approach is then proposed and evaluated. Our proactive study warns of the emergence and proliferation of deep fakes in geography just as "lies" in maps. We suggest timely detections of deep fakes in geospatial data and proper coping strategies when necessary. More importantly, it is encouraged to cultivate a critical geospatial data literacy and thus to understand the multi-faceted impacts of deep fake geography on individuals and human society.