Machine Vision for Climate Change

A workshop at British Machine Vision Conference 2025

The Machine Vision for Climate Change (MVCC) workshop at BMVC 2025 aims to bring together researchers and practitioners at the intersection of computer vision and environmental sustainability. The workshop will explore how state-of-the-art machine vision techniques, spanning deep learning models, satellite imagery, UAVs, video, and remote sensing can be applied to address critical climate change challenges. We invite contributions focused on sustainable infrastructure, renewable energy, biodiversity, forestry, agriculture, disaster response, air quality, and climate-related public health. Emphasis will also be placed on ethical and responsible AI, including fairness, energy efficiency, and interpretability of vision models in climate applications. MVCC seeks to foster interdisciplinary collaboration and highlight the transformative potential of visual intelligence in building a sustainable and resilient future.

We welcome high-quality contributions on the application of machine vision to address climate change and sustainability challenges. Topics of interest include, but are not limited to:

1. Sustainable Built Environment

- Machine vision for sustainable infrastructure, transport and mobility planning

- Vision-based urban design and planning for sustainable cities

- Monitoring and optimizing renewable energy systems using vision technologies

2. Ecosystems and Natural Living Environment

- Automated monitoring of forests, land use, wildlife, and biodiversity

- Computer vision in precision agriculture, yield prediction, and crop health assessment

- Satellite and UAV imagery analysis for land cover and deforestation tracking

- Remote sensing techniques for climate monitoring

3. Climate and Weather Events

- Vision-based air quality monitoring and pollution mapping

- Vision-based earth observation monitoring

- Computer vision for early warning and response to natural disasters

- Visual data analysis for extreme weather prediction and climate-health correlation

- Vision based climate change adaptation and mitigation

- Machine vision applications for climate related public health

4. Vision Models Contributing to Climate Change

- Ethical AI, accountability, and bias mitigation in climate-related vision systems

- Energy-efficient and lightweight models for edge deployment (e.g., on drones)

- Explainable and interpretable vision models in environmental monitoring

- Improving energy utilization for vision model training

Organizing Team:

Dr Lakshmi Babu Saheer

Assistant Professor in Artificial Intelligence

Anglia Ruskin University, UK

Prof Jennifer Schooling

Professor in Digital Innovation and Smart Places

Anglia Ruskin University, UK

Dr Mahdi Maktabdar Oghaz

Assistant Professor in Artificial Intelligence

Anglia Ruskin University, UK

Dr Manu Sasidharan

Assistant Professor in Infrastructure Asset Management

University College London, UK,

Dr Avar Almukhtar

Senior Lecturer in Construction Informatics

Oxford Brookes University, UK

Dr Raul Aquinos Santos

Professor in Flood Monitoring and Detection and International Telecommunication Union (ITU)

Universidad de Colima, Mexico

Keynote Speakers:

Dr David Rolnick

David Rolnick is an Assistant Professor and Canada CIFAR AI Chair in the School of Computer Science at McGill University and a Core Academic Member of Mila. His work focuses on applications of machine learning to help address climate change, particularly in areas such as energy systems, biodiversity conservation, and climate policy. He is a Co-founder and Chair of Climate Change AI and Scientific Co-director of Sustainability in the Digital Age. Dr. Rolnick received his Ph.D. in Applied Mathematics from MIT. He is a former NSF Mathematical Sciences Postdoctoral Research Fellow, NSF Graduate Research Fellow, and Fulbright Scholar, and was named to the MIT Technology Review's 2021 list of "35 Innovators Under 35."

Dr Mehran Eskandari Torbaghan

Dr Mehran Eskandari Torbaghan is an Assistant Professor in Infrastructure Asset Management at the Department of Civil Engineering with a Doctor of Philosophy (PhD) focused on risk management and linear infrastructure systems from University of Birmingham. Mehran spent five years in the civil engineering industry, as a geotechnical engineer, before returning to academia to study a master’s in construction management and then the PhD both at the University of Birmingham. He then worked as a research fellow at the University of Birmingham for around five years, before becoming a lecturer. Mehran has been engaged in supervising a number of PhD students. His research portfolio and interest lie in the field of smart management of infrastructure systems, investigating the application of robotics and autonomous systems for condition monitoring and repair of urban infrastructure.

Dr Manuel Herrera

Dr Manuel Herrera is a Lecturer in Hydrology at Newcastle University, where his research utilises AI, data-driven models, and complex network analysis to develop asset management and climate change adaptation strategies for water infrastructure. With expertise in AIoT and AI-driven decision-making for urban systems and the built environment, Dr Herrera's work extends to other critical infrastructure, such as communications and transport networks. A Fellow of the Royal Statistical Society (RSS) and a committee member of the RSS Special Interest Group in Statistical Engineering, Dr Herrera's contributions have earned him recognition, including being ranked among the top 2% of global researchers in 2021 by Stanford University, particularly in AI, Engineering, and Communication Technologies.

Important Dates:

Submission Deadline: July 25, 2025

Notification of Acceptance: August 29, 2025

Camera-ready Submission: September 29, 2025

Workshop Date: November 27, 2025

0d 0h 0m 0s to submission deadline!

Submission Guidelines:

The Machine Vision for Climate Change (MVCC) workshop follows the submission guidelines, template, and regulations of the British Machine Vision Conference (BMVC). For more information, please refer to the following link:

Submission Guidelines

Submit Your Work:

Please use the following link to submit your work through CMT submission system:

Submit Your Work Here!

Contact Us:

For any inquiries regarding the conference, please feel free to contact the organising committee at mvcc.bmvc@gmail.com. We are happy to assist with any questions related to submissions, registration, or participation.

The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.