Understanding the sensitivity of vegetation density and carbon storage estimates from terrestrial laser scanning to leaf-wood classification accuracy

Entry requirements

Please use this Research Proposal, Personal statement and CV writing guide when preparing an application.

Months of entry

Anytime

Course content

Due to their importance for climate change monitoring, modelling, and adaptation, the Global Climate Observing System (GCOS) designates several vegetation structural properties as ‘essential climate variables’ (ECVs), including leaf area index (LAI) and above-ground biomass (AGB). As a measure of vegetation density, LAI controls the size of the interface between the biosphere and atmosphere, the interception of light, and photosynthesis. Meanwhile, AGB is a vital parameter for carbon budgeting, describing terrestrial carbon sink. Rapidly acquiring millions of point measurements representing the physical environment in three dimensions, terrestrial laser scanning (TLS) has become an increasingly popular method for estimating LAI and AGB in recent years.

To determine LAI and AGB from TLS data collected during leaf-on conditions, points must first be classified as leaves or wood. Existing leaf-wood classification approaches applicable to TLS point clouds can be divided into geometric and intensity-based methods, and suffer from several limitations. Geometric methods require high resolution scans and typically apply at the level of an individual tree, requiring segmentation of the point cloud (Calders et al., 2020). Notably, recent work revealed the majority of geometric methods misclassify small branches and twigs as leaves (Chen et al., 2025). Meanwhile, intensity-based methods are confounded by natural variability in the reflectance of leaves and wood, bidirectional reflectance effects, and the need for complex radiometric calibration (Danson et al., 2018). By utilising laser scanners capable of dual-wavelength and/or waveform sensing, there may be potential for some of these limitations to be overcome.

Despite these known limitations, the sensitivity of TLS-derived estimates of LAI and AGB to the accuracy of leaf-wood classification (as well as potential implications for carbon budgeting) remains relatively underexplored. This project will evaluate a range of geometric and intensity-based leaf-wood classification approaches, with the aim of better understanding this sensitivity. The project will involve field and laboratory work within the United Kingdom, making use of the School’s newly acquired state-of-the-art RIEGL VZ-600i TLS, as well as the world’s first dual-wavelength, full-waveform TLS, the Salford Advanced Laser Canopy Analyser (SALCA) (Danson et al., 2018).

Information for international students

Open to international students

Fees and funding

Applications for this project are welcomed from anyone worldwide, but there is an opportunity for UK candidates (or those eligible for UK fees) to apply for a widening participation scholarship. These scholarships are targeted at increasing participation from groups currently underrepresented within research and priority will be given to students that meet one or more of the widening participation criteria. Priority will also be given to University of Salford graduates.

To enquire about University of Salford funding schemes – including the Widening Participation Scholarship – visit this website