Generative Adversarial Networks in the built environment: A comprehensive review of the application of GANs across data types and scales

AN Wu, R Stouffs, F Biljecki - Building and Environment, 2022 - Elsevier
Abstract Generative Adversarial Networks (GANs) are a type of deep neural network that
have achieved many state-of-the-art results for generative tasks. GANs can be useful in the …

The politics of pixels: A review and agenda for critical remote sensing

MM Bennett, JK Chen… - Progress in Human …, 2022 - journals.sagepub.com
We offer a review and research agenda for critical remote sensing, defined as inquiries and
scientific practices cognizant of the embedding of power within the production, analysis, and …

Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook

X Zou, Y Yan, X Hao, Y Hu, H Wen, E Liu, J Zhang… - Information …, 2025 - Elsevier
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …

Accelerating ethics, empathy, and equity in geographic information science

TA Nelson, MF Goodchild… - Proceedings of the …, 2022 - National Acad Sciences
Science has traditionally been driven by curiosity and followed one goal: the pursuit of truth
and the advancement of knowledge. Recently, ethics, empathy, and equity, which we term …

GANmapper: geographical data translation

AN Wu, F Biljecki - International Journal of Geographical …, 2022 - Taylor & Francis
We present a new method to create spatial data using a generative adversarial network
(GAN). Our contribution uses coarse and widely available geospatial data to create maps of …

Exploring the limitations in how ChatGPT introduces environmental justice issues in the United States: A case study of 3,108 counties

J Kim, J Lee, KM Jang, I Lourentzou - Telematics and Informatics, 2024 - Elsevier
The potential of Generative AI, such as ChatGPT, has sparked discussions among
researchers and the public. This study empirically explores the capabilities and limitations of …

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

Y Kang, S Gao, RE Roth - Cartography and Geographic …, 2024 - Taylor & Francis
The past decade has witnessed the rapid development of geospatial artificial intelligence
(GeoAI) primarily due to the ground-breaking achievements in deep learning and machine …

Deepfakes: An integrative review of the literature and an agenda for future research

PN Vasist, S Krishnan - … of the Association for Information Systems, 2022 - aisel.aisnet.org
We are witnessing a growing concern around the impact of hyper-realistic synthetic media
and its dissemination in what is widely known as" deepfakes." However, the phenomenon's …

Translating street view imagery to correct perspectives to enhance bikeability and walkability studies

K Ito, M Quintana, X Han, R Zimmermann… - International Journal of …, 2024 - Taylor & Francis
Street view imagery (SVI), an emerging geospatial dataset, is useful for evaluating active
transportation infrastructure, but it faces potential biases from its vehicle-based capture …

The ethics of ai-generated maps: A study of dalle 2 and implications for cartography

Y Kang, Q Zhang, R Roth - arxiv preprint arxiv:2304.10743, 2023 - arxiv.org
The rapid advancement of artificial intelligence (AI) such as the emergence of large
language models including ChatGPT and DALLE 2 has brought both opportunities for …