Tree Mortality Maps to Assess Fire Risk

Submitted by tadamson on

Tens of millions of trees reportedly died in California during the 2012–2016 drought, resulting in marked increases in heavy fuel loads on the landscape. In conjunction with warming temperature, drier conditions, and over a century of fire suppression, the accumulation of fuels can result in large fires that are beyond the predictive capacity of traditional fire behavior models. These extreme fires can cause an enormous amount of damage. One example is the 2020 Castle Fire, which burned into numerous giant sequoia groves at unprecedented severity. Preliminary estimates suggest the fire may have killed over 13–19% of all large (greater than ~1 meter in diameter) sequoias in the species range.

Developing treatments to reduce the likelihood of these fires requires landscape-scale assessments of catastrophic fire risk. U.S. Geological Survey (USGS) scientists and partners have launched a collaboration with a statewide consortium to produce fire risk maps at Sequoia and Kings Canyon National Parks (SEKI) using in-development, next-generation fire behavior models. Production of these risk projections will require robust empirical data that quantify existing fuels, including an accurate map of drought-caused tree mortality. USGS scientists are currently working with the U.S. Forest Service Region 5 Remote Sensing Lab (RSL) and the National Aeronautics and Space Administration Jet Propulsion Laboratory to develop high-quality dead-tree maps using remote sensing data from the Global Airborne Observatory (GAO), Landsat, Sentinel, and the National Agriculture Imagery Program.

Ground-based data collection is focused in two GAO study areas that cover large portions of the conifer forests at SEKI as well as in plots being established as part of a fuels assessment program across the range of conifer forests at SEKI. The ground-based data collections include precise tree locations, tree species, and tree status (live or dead). The research team is working with various groups to combine these data with remote sensing measures to develop dead tree maps as well as species maps. USGS will then collect additional data to validate the map. This adaptive process will continue until acceptable levels of accuracy are reached.  The project description is available here.

Preliminary species map for mixed conifer forest in the Sierra Nevada, with dead trees shown in black. Associated project information is available here

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Author Name
Adrian Das
Author Email