DrPhilippa Mason

Research activities and interests

My research interests are broad and include the InSAR, planetary geoscience, spectral geology, tectonic geomorphology, geohazards and the application of remote sensing and data science/machine learning to a variety of geoscientific fields.

I am a member of the Geohazards Research Group here in ESE, and of the Engineering Scale Geology Research Group ESGRG, an interdepartmental group focused on small scale geological problems affecting civil engineering activities.

I have been a member of the Envision mission proposal team since 2010, and since the mission was selected by the European Space Agency in 2018, I served as a member of the Science Study Team (SST) in Phases A and B1. In 2022, I was appointed by NASA as a member of the VenSAR Science Team (VeST) and in 2025 was appointed by ESA as one of six Inter-Disciplinary Scientists on Science Working Team of the Envision Venus mission in Phase B2. NASA looks set to withdraw from the mission and so a new European radar will replace it. This instrument will be called VeraSAR and in Jul 2026 I was appointed to the VerSAR instrument team to assist in the instrument's development.

Envision is an ESA funded M5 mission heading to Venus to explore and better understand the planet as a system. The mission will use Synthetic Aperture Radar (SAR), SubSurface Radar Sounding and multispectral NIR imaging of emissivity to image the surface, in a similar way to those we use routinely on Earth, to better understand the tectonic, surface and internal structure of Venus, and thereby to better understand its history as a planet seemingly inhospitable to life, as well as to detect current geological activity. The instrument payload also includes UV and IR spectrometers aimed at exploring Venus' atmosphere, clouds and climate, as well as a Radio Science Experiment, to better understand the interior structure of the planet. Hence Envision will investigate Venus form the cloud tops down to the core!

My research focuses on the development and refinement of next generation software tools to detect changes and characterise terrains at Venus, in a robust and automated way, to prepare for the mission science phase which begins in 2034. This research, and two new Post-Doctoral Researchers who have joined my team, are generously funded by the UK Space Agency.

My Earth-bound research is focused mainly on the development and application of InSAR techniques to the understanding of small-scale ground deformation. I have research students working with persistent scatter InSAR techniques to measure and monitor small scale ground movements in natural and man-made environments. I have recently completed the publication of the first national guidelines document on the use of Earth Observation and InSAR in infrastructure and civil engineering, as lead author of an international team from academia and industry. My research also involves the use and development of remote sensing to a variety of environmental challenges. This includes the use of cosmogenic nuclides to reconstruct ice retreat history in Antarctica; and in the use of machine learning to extract environmental information from global Earth Observation data.

Current Research

Venus and Envision (funded by ESA and UKSA):

- SAR processing software development for the Envision mission to Venus (2 x PDRA: Dr Gao & Dr Awasthi)
- Development of robust Venus radar change detection tools (2 x PhD: Gallardo i Peres & Davidova)

Earth Observation tools, applications and developments:

- Development of Machine Learning approaches to assumption free models for time-series InSAR processing (Zhang, PhD)
- Developing Machine Learning approaches to change detection tracking of atmospheric methane plumes (Xu, PhD)
- Evaluating impacts of climate change on sustainable agriculture and desertification in Najran province, Saudia Arabia (Alquraishi, PhD)
- Predicting slope failures at coastal assets in multi-temporal airborne LiDAR data using machine learning (Widodo, PhD)
- Unsupervised crop mapping using Earth Observation optical and SAR data with Machine Learning (Li, PhD)
- Tracking coral reef bleaching in satellite images and Machine Learning (al Zayer, PhD)
- Tracking of climate change variables using Machine Learning (Prasow-Emond, PhD)