Detecting Fake Aerial Imagery – Call for participants

post by Matthew Yates (2018 cohort)

Hello everyone! I’m a 3rd year Horizon CDT PhD student partnered with the Defence Science and Technology Laboratory (Dstl). My PhD project is about the detection of deep learning generated aerial images, with the final goal of improving current detection models.

For this study, I am looking for participants to take part in my short online study on detecting fake aerial images. We have used Generative Adversarial Networks (GANs) to create these.

I am looking for participants from all backgrounds, as well as those who have specific experience in dealing with either Earth Observation Data (e.g. aerial imagery, satellite images) or GAN-generated images.

Purpose: To assess the difficulty in the task of distinguishing GAN-generated fake images from real aerial photos of rural and urban environments.  This is part of a larger PhD project looking at the generation and detection of fake earth observation data.

Who can participate? This is open to anyone who would like to take part, although the involvement of people with experience dealing with related image data (e.g. satellite images, GAN images) is of particular interest.

Commitment: The study should take between 5-15 minutes to complete and is hosted online on

How to participate? Read through this Information sheet and follow the link to the study at the end.

Link to study:  Detecting Fake Aerial Imagery

For any additional information or queries please feel free to contact me:

Thanks for your time,

Matthew Yates