Evaluating Landscape Change Following Catastrophic Fires in National Parks

Submitted by tadamson on

Recent catastrophic wildfires in the western United States have led to loss of life and property and burned through some of the most iconic landscapes in the National Park Service (NPS). This ongoing project assesses the impact of three fires in national parks in California: the 2018 Carr Fire, which burned 97% of the Whiskeytown National Recreation Area across mixed coniferous communities; the 2020 Caldwell Fire, which burned 70% of Lava Beds National Monument across sagebrush and native grasslands; and the 2020 Dome Fire, which burned over 43,000 acres in the Mojave National Preserve, damaging one of the most extensive and robust stands of Joshua trees. The U.S. Geological Survey (USGS) is providing technical support and using multi-scale remote sensing tools to assess 1) fire impacts to vegetation and cultural resources and 2) vegetation landscape recovery or change. USGS staff are conducting field surveys of topography (using Real Time Kinematic GPS), fire effects on vegetation, and post-fire vegetation recovery. Results of the field surveys are being paired with data collected using uncrewed aircraft systems (UAS) and satellite imagery to create products at different spatial scales. This information is being used by NPS staff to inform management intervention and plan for recovery. In 2022, WorldView-2 imagery was acquired for Lava Beds National Monument and Mojave National Preserve to delineate the fire extent across these remote regions. UAS acquisition of orthoimagery occurred in Whiskeytown for the third sampling year and is being paired with Landsat imagery to estimate forest change and recovery. Field surveys were conducted for ground validation purposes at all three locations. With the continued threats of wildfire to Department of Interior lands, a multi-scale approach can help inform understanding of ecosystem change, landscape conversion, and management intervention to prevent invasive species expansion.

3D dense point cloud created from uncrewed aircraft system (UAS) surveys and processed with structure-from-motion software. The dense point cloud is the base for derived products such as orthoimagery and digital elevation models. 

Disclaimer: Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Author Name
Karen Thorne
Author Email