Current and Recent Projects

Geospatial Data Products to Support Fuel Treatment Planning and Monitoring

Wall-to-wall, large scale measurements of forest structure and fuel conditions with higher spatial resolution, dynamism, and accuracy are needed to improve understanding of forest response to climate change and management and to support fuel treatments to restore fire-resilient forests. Newly-available remote sensing datasets and processing infrastructure have significantly enhanced the capacity to address these needs. In this study, we are using remote sensing to develop geospatial data products that will quantify forest structure (forest cover, ladder fuels) and forest type and their annual dynamics. We are achieving this by developing models that will predict these attributes – as measured from field data collection, and publicly-available airborne LiDAR - from both active (SAR) and passive (multispectral imagery) satellite remote sensing. Our system will be updated on annual basis to allowed for continued annual monitoring and analysis of fuel treatment effectiveness and fuel treatment impacts on Mexican spotted owl habitat. This work is a collaboration with Matthew Hurteau, Gavin Jones, Hans Andersen, and Harold Zald and is funded by the Joint Fire Science Program. We are currently looking for a postdoc and PhD student interested in joining this project in Spring 2024 (postdoc) and Fall 2024 (student). If you are interested, fill out this form.

Disturbances and carbon in western US forests 

Forests in the western US store significant quantities of carbon and this carbon is vulnerable to be released to the atmosphere through disturbances that have been become more severe as a result of climate change and past management. Both the amount of carbon, and the vulnerability of that carbon to different types of disturbances varies substantially among forests in the western US, requiring alternative management strategies in different forest types. In this project, we are using datasets derived from remote sensing to estimate forest structure and fuel conditions and quantify their roles in recent disturbances in western US watersheds. Thus far, we have found that in western US coniferous forest watersheds from 2001-2020, the area burned at high severity increases with increasing forest cover and connectivity and decreases with increasing heterogeneity (Francis et al. 2023). This work is funded by the Environmental Defense Fund. Previous collaborators on this project included Brandon Collins, Pariya Pourmohamadi, and Zack Steel, and current collaborators include Matthew Hurteau, and Chang Gyo Jung. 

Testing a simple forest demographic model with airborne lidar data and forest inventory data from the Wind River Forest Dynamics plot

Forest demographic models have traditionally been tested against measurements of forest structure derived from field inventory data. However, remote sensing can effectively measure some aspects of forest structure that are difficult to quantify through field data collection, and these alternative measurements of forest structure from remote sensing can test alternative aspects of forest demographic model predictions and thereby improve understanding of forest demography. In collaboration with Caroline Farrior from UT Austin and Jim Lutz from Utah State University, I developed an algorithm to test predictions of canopy height from a forest demographic model against observations of canopy height from airborne LiDAR and scaled from forest inventory data. We discovered that accounting for the higher mortality rate of large vs. intermediate trees (i.e. the U-shaped mortality curve) that was present in the forest was essential to accurate predictions of forest canopy height. However, the importance of the U-shaped mortality curve to forest structure has been underappreciated, because most prior studies had tested model predictions against field-measured tree diameter distributions only (Francis et al. 2023).

Measurements of forest structure: from traditional field measurements to measurements from remote sensing

 New remote sensing technologies have enabled a range of new measurements of forest structure, with various grain sizes and spatial extents. These new measurements add to a large body of field-based measurements of forest structure. In this paper, we reviewed measurements of forest structure currently available from both field-based methods and from various remote sensing platforms, discuss advantages and limitations of each, and future directions for integrating forest structural measurements into ecological frameworks (Atkins et al. 2023). This work was led by Jeff Atkins (USFS Southern Research Station) and was an outcome of an NSF funded workshop on forest structural diversity. 

Past projects

We are working on including past projects in this section. In the meantime, if you are interested in past projects, please check out the 'Publications' page!