Deep fake geography? When geospatial data encounter Artificial Intelligence

TLDR

The convergence of AI and GIScience raises concerns about deep fake geography and its potential to reshape human perception of the geographic world. The paper aims to dissect the algorithmic mechanisms behind falsifying satellite images and to demonstrate a robust deep‑fake detection approach. An empirical study was conducted to analyze how satellite images can be falsified with non‑existent landscape features, and a novel detection method was proposed and evaluated. The study warns of the growing prevalence of deep‑fake geography, recommends timely detection and coping strategies, and urges cultivation of critical geospatial data literacy to mitigate its societal impacts.

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.