Research
My research addresses the intersection of advanced remote sensing (terrestrial laser scanning, airborne & drone photogrammetry/LiDAR), fire and fuel-treatment science, vegetation structure and habitat modelling, and passive restoration processes in forest and riparian ecosystems. I work to develop rigorous metrics, workflows, and empirical evaluations that bridge sensor data to ecological and management outcomes — whether in wildfire treatment effectiveness, habitat‐structure quantification, or ecosystem recovery. My work contributes to both applied management questions and fundamental understanding of structural complexity, ecological resilience, and forest/habitat change.
Research Summaries
Wildfire Treatment Outcomes
A major programme titled Empirical Assessments of Wildfire-Treatment Outcomes evaluates the effectiveness of vegetation and fuel treatments when subsequently exposed to wildfire. The research develops a scalable, reproducible workflow linking variables such as climate, weather, topography, vegetation/fuels, and treatment characteristics to outcomes including burn severity, wildfire spread containment, and impacts to communities & infrastructure.
This work supports decision-making on where and how fuel treatments can deliver the greatest resilience under warming conditions.
Wildlife Habitat Modelling
Remote sensing methods—including TLS and airborne LiDAR—are used to measure finescale structural features relevant for wildlife habitat, such as shrub cover, understory connectivity and horizontal/vertical complexity. These structural metrics inform species-specific habitat modelling (e.g., for the Canada lynx), linking sensor data to conservation and management applications.
Drone Work for Fire Outcomes at Various Canopy Heights
Unoccupied aerial systems (UAS) equipped with multispectral photogrammetry or LiDAR are applied to capture three-dimensional point clouds of post-fire conditions across canopy height strata. This allows quantification of upper canopy removal, mid‐canopy changes and ground‐surface responses to fire, thereby improving understanding of fire severity and structural change across vertical layers.
https://fireecology.springeropen.com/articles/10.1186/s42408-025-00375-2
TLS Work to Quantify Fuel Moisture
Terrestrial laser scanning (TLS) is leveraged not only for structural measurement but also for characterising fuel-state, specifically litter fuel moisture content. By analysing TLS intensity and return signatures, the work demonstrates that TLS can provide remote sensing pathways for mapping fuel moisture — a crucial input for fire behaviour modelling.
Novel TLS Metrics for Forest Structure
New metrics derived from single-station TLS scans—namely depth, openness and isovist—have been developed to quantify forest structural complexity with high precision and minimal observer bias. These metrics enable robust quantitative differentiation of forest structure across ecoregions, support ground truthing of airborne LiDAR models, and track structural change in response to management or natural processes.
https://www.mdpi.com/2072-4292/15/1/145?utm_source=chatgpt.com
Passive Restoration Recovery from Cattle Browsing
Investigations of riparian zones following cattle exclusion document vegetation recovery (willows, rushes, reduced bare soil and erosion) under passive restoration conditions. The research highlights ecosystem resilience mechanisms in grazing-impacted systems and informs restoration policy and monitoring of long-term trajectories in riparian settings.
https://link.springer.com/article/10.1007/s00267-014-0436-2
Interactive map hosted by OSU: https://www.cof.orst.edu/cof/fr/research/hart/index.html
This work was also featured as part of the documentary “Rewilding a Mountain“
