Using drone LIDAR technology to quantify hedgerow management, quality and configuration, and the impacts on farmland pollinator communities

The use of emerging technology in agri-environmental systems is gaining momentum and there's a need to train up the next generation of researchers and land managers in fast advancing technological expertise whilst providing them a firm foundation in the practical applications of such technology. This project will combine expertise in drone LIDAR technology to help map key habitats (i.e hedgerows) within the farming landscape, quantify how different agricultural management regimes impact the quality and configuration of hedgerows and assess the impact of hedgerow quality on the abundance and diversity of key farmland pollinators.

Drone LIDAR will be used for High-Resolution 3D Mapping of the landscape by capturing fine details to assess the height, width, and overall structure of hedgerows. LIDAR data enables assessment of hedgerow density and health by distinguishing different vegetation types and can reveal areas of low or high vegetation density which is crucial for understanding hedgerow quality.

In addition, Drone LIDAR can help determine how effectively hedgerows connect different parts of the landscape, and identify gaps or disruptions in the hedgerow network, which are known to impact the abundance and diversity of farmland biodiversity including pollinators and other beneficial insects.

The hedgerow and landscape quality metrics will then be linked to on site assessment of farmland pollinator communities which are key to delivery of critical crop pollination services. We will focus on both diurnal and nocturnal insects (i.e. bees and moths) and use conventional field methods as well as emerging technology such as image recognition to characterise these insect communities such as AMI-traps attracting and imaging moths at night.