
Dr Ce Zhang
MSc (ITC), MSc (Soton), PhD (Lancaster)
Expertise
AI and data science techniques to tackle the most pressing environmental and socio-ecological challenges of our time
Current positions
Senior Lecturer
School of Geographical Sciences
Contact
Press and media
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Research interests
I am a Senior Lecturer in Environmental Data Science at the School of Geographical Sciences, University of Bristol. My research develops and applies GeoAI, machine learning and Earth observation methods to understand, predict and support decisions about environmental and socio-ecological change. I am particularly interested in multimodal and foundation-model approaches that integrate satellite, airborne, street-level and other geospatial data. My work spans physical and human geography and connects geospatial science with computer science, ecology and environmental science, with a broad range of applications across ecosystem monitoring and restoration, climate and environmental hazards, urban systems, and sustainable land-use planning and decision making.
Four major themes of my research are:
- GeoAI, Foundation Models and Multimodal Learning
- Remote Sensing and Environmental Intelligence
- Environmental Change, Ecosystems and Climate Hazards
- Spatial Decision Intelligence for Socio-ecological Systems
At the University of Bristol, I am the Co-lead for Environmental Change Research at the Cabot Institute for the Environment and Co-Theme Lead for AI for Climate Hazards within the Met Office Academic Partnership (MOAP).
I am Specialty Chief Editor for Image Analysis and Classification at Frontiers in Remote Sensing, a Topic Editor in Earth Observation, and serve on the editorial boards of several leading international journals.
PhD supervision
At Bristol, my research group develops interdisciplinary GeoAI approaches for environmental and socio-ecological applications. I currently supervise the following PhD students:
Megan Bulpitt: AI for flood mapping and socioeconomic vulnerability.
Yaoguang Yang: Geospatial AI for coastal mapping and modelling.
Zhiyue He: Cross-modal approach to flood segmentation and modelling.
Jianduo Chai: Autonomous sensing for environmental observation using UAV.
Boyi Li: Vision language models in remote sensing.
James Brock: Foundation models in forest change analysis.
Yifan Liang: Modelling green space and mental health using Street View imagery.
Holly Liken: AI for algal monitoring in freshwater ecosystems.
Recent PhD Completion
Ziming Wang: Flood mapping and modelling using Earth observation and geospatial science.
Nikolaos Tziokas: Monitoring urban resilience using fine-resolution satellite nighttime light imagery.
Kennedy Kanja: Monitoring forest above ground biomass in Miombo woodlands of Zambia.
PhD recruitment
I welcome enquiries from prospective PhD students with a strong background in geospatial science, artificial intelligence, data science, computer science, statistics, or related areas.
If you are interested in working with me, please email ce.zhang@bristol.ac.uk with the following materials:
- your CV, including previous degrees and grades, research experience, publications, and relevant awards;
- a concise research proposal (approximately 1-2 pages) outlining the research question you would like to investigate, the proposed data and methodology, and how the project relates to my research interests;
- a sample of your academic writing, such as a published or submitted paper, dissertation, thesis chapter, or other substantial piece of research writing.
I use these materials together to assess applicants’ academic background, research potential, methodological thinking, and written communication. Please note that, due to the large volume of enquiries I receive, I am normally unable to respond to emails that contain only a CV or do not include sufficient information about the proposed research.
Depends on the proposed topics, applications may be made through the PhD in Geographic Data Science, PhD in Physical Geography or PhD in Human Geography. A range of University and external funding opportunities are available each year.
Applicants from China are particularly welcome to contact me regarding the China Scholarship Council-University of Bristol PhD Scholarship. For the current round, the University application deadline is 12 noon (UK time) on 30 November 2026. I also welcome enquiries from CSC-funded visiting students and scholars where their proposed research aligns closely with my group.
Projects and supervisions
Research projects
UKRI Smart Data Research Fellowship: Geospatial AI for sustainable biomass expansion and decarbonisation in the UK
Principal Investigator
Description
Meeting the UK’s net zero carbon emissions by 2050 will require rapid changes in how we produce energy and materials. Alongside wind, solar and other renewables, one of the most…Managing organisational unit
School of Geographical SciencesDates
01/02/2026 to 31/07/2027
STFC IAA: Leveraging AI and Earth Observation for Strategic Heat Network Planning in the UK
Principal Investigator
Managing organisational unit
School of Geographical SciencesDates
01/04/2024 to 30/09/2025
European Union Horizon programme: Modern Approaches to the Monitoring of BiOdiversity (MAMBO)
Role
Co-Investigator
Managing organisational unit
Cabot InstituteDates
01/08/2022 to 01/08/2026
NERC Landscape Decision Programme: Explainable AI for UK agricultural land use decision-making
Role
Co-Investigator
Managing organisational unit
Cabot InstituteDates
01/12/2019 to 30/11/2020
Thesis supervisions
Publications
Selected publications
27/08/2026Uneven urban resilience across economic sectors revealed by satellite nighttime lights
Communications Earth & Environment
Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape
Nature Communications
Identifying and mapping individual plants in a highly diverse high-elevation ecosystem using UAV imagery and deep learning
ISPRS Journal of Photogrammetry and Remote Sensing
Recent publications
01/08/2026A hybrid spatial-temporal data model for indoor dynamic path planning in a 2D/2.5D environment
Geo-Spatial Information Science
A Semi-Supervised Self-Organised Prototype Tree-based Method for Few-Shot Remote Sensing Scene Classification
Knowledge-Based Systems
BlinkChange: Active Perception Bi-temporal Reliable Representation for Disaster Impact Understanding from Remote Sensing Imagery
ISPRS Journal of Photogrammetry and Remote Sensing
Continuous change monitoring of supraglacial lakes during melt and non-melt seasons with multi-source satellite imagery and deep learning
International Journal of Applied Earth Observation and Geoinformation
Cross-Layer Feature Fusion and Attention-Based Class Feature Alignment Network for Unsupervised Cross-Domain Remote Sensing Scene Classification
Remote Sensing



