We’re researching new ways to capture and extract geospatial data, new detail to collect and support the ever-expanding requirements of the digital world, and new means to manage and present this information.
What we do
Mobile mapping and feature extraction
We’re using vehicles equipped with sensors to capture geospatial data and changes to our environment in 3D. This spans road vehicles through to unmanned aerial vehicles. For example, we have a partnership with Intel Mobileye to explore what we can map with vehicle cameras. This can help us map our street environments in much greater detail, connecting localised Internet of Things (IoT) technology to the wider environment in which it sits.
We’re investigating ways to use artificial intelligence to extract this information about features in the landscape from raw data, extracting more from our aircraft imagery and paving the way to collecting additional detail from unmanned aerial vehicles.
And we’re always scanning the horizon for future opportunities, such as quantum gravity sensing to map buried assets such as sewers or voids such as unrecorded tunnels.
This knowledge will underpin our mobile and connected society.
The highly detailed, 3D geospatial information needed to support emerging digital technologies and economy will come from multiple data sources – from street-level and from the air. We’re investigating ways to fuse together data from multiple sources to provide an integrated view of the world. 3D information may come from other domains too and we’ve been involved in research in Singapore about re-using 3D building construction models as inputs for geospatial information.
We need to be able to do this to keep track of long-term change as new buildings and new infrastructure such as roads and utilities are built. We also need to manage and communicate temporary changes, for example passing data between connected and autonomous vehicles about changes in road conditions. Research into techniques in automatic change detection in different environments is key to this.
Our data updates may feed into human decision making or artificial intelligence systems.
Sometimes the best resource for data collection is people. Different communities hold vital local knowledge, including informal nicknames for places – which can save valuable time in emergency and rescue scenarios.
Sometimes the crowd might be the general public and at other times, a particular section of it. For example people on social media sharing what’s going on in certain places; or expert groups, such as emergency services personnel, sharing knowledge about the regions they cover. It’s important to understand what different information different communities can provide, and the different biases that might be involved.
Secure and reliable information
Whether data is coming directly from people, from the services they use, or from devices monitoring the environment around us, we need reliable information and people should rightly expect that their location information is private.
We are involved in privacy, security and trust of geospatial data. Helping to ensure it is transferred accurately between connected and autonomous vehicles, in logistics, and in smart infrastructures, such as highly instrumented buildings where we can track resource use in detail.
Want to work with us?
We are working with universities, students and industry to advance our use of geospatial data and technologies. Get in touch to be involved.