
By Madeleine Gregory
Wildfires have been increasing in frequency and size across North America in recent years. British Columbia is no exception to that trend; more than 4% of the heavily-forested province has burned since 2017. In 2023, Canada saw its worst wildfire season in recorded history. These high intensity fires affect ecosystem health and local economies, as timber is a major industry in BC.
Sarah Smith-Tripp, a PhD candidate at the University of British Columbia, Canada is interested in exploring how forests recover from major blazes. Traditional monitoring involves people going out to measure the regrowth of forests, which is difficult and time-intensive, especially in remote forests. To monitor forest regrowth from afar, Smith-Tripp examined Landsat images from early on after a fire, analyzing how different patches of forest showed different spectral responses. Then, she linked these spectral responses to drone-collected lidar data, which allows you to measure the structure of a forest easily and rapidly after a disturbance like fire. Using drone-acquired lidar to track how the structure of a forest changes in the decades after a fire, she was able to use those early spectral responses to predict different trajectories of forest development post-fire. You can read more about the research here. The findings of Sarah’s research can help forest managers and policy makers strategize on the most effective post-fire management action, such as prioritizing areas for post-fire planting.
What is one major takeaway from your research?
The major takeaway from my research is that we can use Landsat data to identify unique recovery responses early on (+5 years) after wildfires. These early responses ultimately indicate longer-term differences in our future forests. This is important because it means that Landsat can help us better understand the future of our forests after high-severity wildfires.
Why did you use Landsat in this work? Did it give you any insight that would have been difficult to get otherwise?
The historical legacy of the Landsat series of satellites is pivotal for this work. My research investigates how spectral responses from the first five post-fire years, as captured by Landsat, can describe longer-term forest conditions—up to 21 years post-fire! To do this work, we need long-term consistent data. Landsat is the only satellite series that can provide decades of data at 30 m resolution across a range of spectral bands.
What is the benefit of blending Landsat and lidar data?
Landsat sensors provides detailed information on surface reflectance of the land’s surface. Managers may want additional information on tree density or composition, which we can derive from lidar data. For example, near-infrared surface reflectance provides insight into the overall amount of photosynthesis on the landscape, but does not provide information on what plants are contributing to the spectral response. When we link Landsat data with lidar data we can understand how differences in spectral responses relate to differences in forest structure, such as the density of coniferous stems. After I use lidar data to estimate forest structure at different points post-fire, I then link that to unique spectral responses from Landsat. This allows us to describe different trajectories of forest growth post-fire. For example, one trajectory is that of delayed conifer regrowth, where conifers take 8-10 years to establish on the landscape.
How does understanding these post-fire forest-structures help inform future recovery efforts?
By incorporating the information from my research, we can characterize recovery over large regions, helping land managers both prioritize management areas and plan for the future. We can use my approach to identify areas that may have particularly slow coniferous regrowth, which could be alleviated with planting. We can also identify areas that will have particularly dense coniferous growth, which pose a risk of future short-interval reburn.
Are there any research questions you’re interested in that build off of this work?
I am particularly interested in ways that we can better capture soil burn severity and how this will impact future forest growth. Many studies have found that there is a strong link between soil burn severity and deciduous growth. Soils that burn at high severity are also more vulnerable to erosion and landslides. However, satellite-based measures of burn severity struggle to accurately capture how a fire impacts the soil. Currently, the USGS adjusts satellite measures of burn severity using specially-trained soil scientists to ground truth each fire event (see details on the BAER response team here: BAER). However, with the additional bands included in the Landsat Next mission alongside improved remote sensing of high-intensity fire events provided by additional private and public satellites, I think there is a possibility to better capture soil burn severity. Ideally, this means that we could better monitor both soil and vegetation recovery after fire.
First author:
Sarah Smith-Tripp
Ph.D. Candidate, University of British Columbia
Co-authors:
Nicholas C. Coops
Professor, University of British Columbia
Joanne White
Research Scientist, Canadian Forest Service, Natural Resources Canada
Christopher Mulverhill
Postdoctoral Fellow, University of British Columbia
Sarah Gergel,
Professor, University of British Columbia
Funding Acknowledgement: NSERC Alliance project Silva21 NSERC ALLRP 556265 –2
Smith-Tripp, S., Coops, N.C., Mulverhill, C., White, J.C., Gergel, S., 2024. Early spectral dynamics are indicative of distinct growth patterns in post-wildfire forests. Remote Sensing in Ecology and Conservation, https://doi.org/10.1002/rse2.420=