Name: Lyndsey Graham
Project Title: “Optimising Hedgerow Structure for Biodiversity: Developing and Testing LiDAR Based Structural Condition Models”
I am interested in agri-ecosystems and the role of agri-environmental schemes and management decisions at different scales which have an effect on farm wildlife and habitat. This includes interests in habitat fragmentation, landscape and habitat connectivity, landscape structure, remote sensing, hedgerow and field margins.
Prior to my PhD I attended Newcastle University obtaining a distinction in MSc Agriculture and Environmental Science and the University of Leeds obtaining a first in BSc Environmental Conservation. In my spare time I am interested in beekeeping, growing vegetables and I am hoping to get some chickens soon.
I chose the IAPETUS doctoral training programme because it offered me a wide range of training opportunities and the chance to belong to a cohort of students going through the PhD process together.
My Research Project
My research is concerned with the agri-environment where hedgerow is an important semi natural habitat, capable of supporting a range of species through variation in habitat quality, influenced in part by structural characteristics. In recognition of the importance of hedgerow active management is encouraged through agri-environment schemes in the UK. However, the effects of such management regimes on elements of hedgerow structure is difficult to quantify, current field survey is based on descriptive, qualitative assessment.
My aim is to determine the potential of terrestrial laser scanning (TLS) to consistently and accurately quantify hedgerow structure; where derived structural variables are both capable of differentiating hedgerows under differing management regimes, and are relevant to wildlife conservation.
My project will benefit from the use of a full-waveform dual-wavelength TLS (SALCA) and a low-cost mobile system (ZEB1). Offering unique opportunities to investigate geometric and spectral properties of the hedgerow, testing and developing processing algorithms capable of extracting structural parameters from point cloud, waveform, intensity and spectral scan data.
Research Areas/Interests: geospatial engineering, remote sensing and photogrammetry, terrestrial laser Scanning, ecology, agri-environment policy
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University Blog: https://blogs.ncl.ac.uk/geospatialengineering/