Images of climate innovation

Hedgerows or climate change heroes?

Using Artificial Intelligence to identify hedgerow gaps, prime for tree planting.

The UK Government calls for afforestation to reduce carbon emissions in the atmosphere. There are massive targets for tree planting and hedgerow restoration but there are no clear nationwide plans for where these trees and hedges will be planted.

Identifying hedgerow gaps for planting brings carbon reduction benefits without the need for large plantations, whilst retaining valuable farming land.

Hedgerows are common across the UK, estimated to be between 400,000 and 750,000 km in length.  However, the location and size of gaps between hedgerows are currently unknown. Gaps present opportunities for tree planting and hedgerow restoration for natural carbon storage (biosequestration), as well as other benefits including increasing biodiversity and flood risk management. Hedgerows are often difficult to map due to the variety of lengths, heights and widths found nationally, introducing uncertainty and ambiguity for measurements on the ground and from remote sensing datasets.

A research team at the University of Hull's Energy and Environment Institute used high-resolution aerial imagery to identify hedgerows using artificial intelligence (AI). AI is commonly used for land use identification, asset detection (planes, ships, cars), and for disaster mapping (wildfire extent, damaged buildings). By teaching an AI model, high-resolution images showing hedgerows and other key landscape features were made through automatic identification.  Adding boundary data enabled the semi-automated extraction of hedgerow gaps for large areas.

Trees and hedgerows absorb and capture carbon dioxide from the atmosphere throughout their lifetime. The Committee on Climate Change has estimated the UK needs to plant 30,000 hectares of trees per year and extend hedges by 40% by 2050 to meet UK Government afforestation targets. This would require large areas of land but by identifying and quantifying hedgerows and hedgerow gaps, Hull's system could pinpoint specific gaps where existing hedges could be restored or spaces filled with new trees.

Hull's AI approach is highly scalable from the local to regional and national scales and could open the door for major afforestation projects to reduce atmospheric carbon and help fight climate change.

Entrant: Josh Wolstenholme , University of Hull

Copyright: Getmapping Plc / EDINA Digimap

Funding: Natural England and the Ferens Education Trust

Collaborators: Freya Cooper, Josh Ahmed, Katie Parsons, Giles Davidson, Rob Thomas, Dan Parsons (Energy and Environment Institute, University of Hull).

Links

https://www.hull.ac.uk/work-with-us/research/Institutes/energy-and-environment-institute

https://www.hull.ac.uk/work-with-us/research/case-studies/hedgerows-mapping-the-gaps