Green Roof Retrofit and Biodiversity Monitoring
This solution was sourced in response to UKGBC’s Innovation Challenge: “How can communities and local authorities implement, maintain, and assess the impact of nature-based solutions to enhance climate resilience?”
Plant species are declining at an alarming rate and a lot of species go unmonitored, however extensive surveying can be prohibitively costly reducing the speed and scale of implementation. Gentian seeks to address these problems through identifying roofs suitable for retrofit and monitoring biodiversity remotely.
Gentian is an innovative new company developing a service that combines satellite-based data with other sources of open or proprietary data, to deliver products to monitor green spaces.
- Their first product is GR ID, which locates buildings with Green Roofs, and sorts these between Intensive/Extensive/Astroturf roofing. It also includes automatic polygon mapping and creating heat maps of habitat density.
- Their second product is GR BD, which assesses various plant metrics on Green Roofs and green spaces, including vegetation condition, habitat categorisation and species identification.
- Their final product is GR RF, which covers identification of roofs that are suitable for Green Roof Retrofitting, using material automatic detection.
Gentian is helping local authorities explore the capacity of new developments and enhance the value of existing properties in a bid to mitigate the loss of biodiversity and the negative impacts of climate change, reduce flooding and improve air quality. Gentian is currently building a product to map the mitigation effects of green infrastructure on stormwater flow, and another product to identify retrofit opportunities for solar panels by calculating installation cost and expected energy production.
All of Gentian’s products are fully remote, and deliver substantial cost and time savings on traditional surveying methods. The social and environmental advantages of Gentian’s services are extensive. It benefits society by enabling local governments to use machine learning to cut down on their costs to taxpayers, making them more efficient and allowing them to hold private sector partners to account. Green spaces in cities have also been associated with better health outcomes for residents by reducing exposure to air pollutants, noise and excessive heat.
Verification & Case Study
Every element of the platform has been proved in the real world. Along the process, several quality checks are performed by internal experts in Remote Sensing, Machine Learning and Urban ecology in order to ensure a quality product.
Case Study: Gentian started work with a grant from the European Space Agency, who have supported it in commercialising research and findings. Now the service is being offered to landowners, developers and local government clients who wish to meet their regulatory requirements and implement urban green infrastructure solutions.