1. Factsheet # 26
Understanding multiscale dynamics of landscape change through the application of remote sensing & GIS
CREATING LIDAR-DRIVEN MODELS TO IMPROVE MANAGEMENT STRATEGIES ON PUBLIC LAND
This research was funded by the Bureau of Land Management
Introduction: Aerial lidar uses laser scanning to provide precise detail of forests across a landscape. Aerial and terrestrial lidar have effectively assessed forest height inventory (Andersen et al. 2006; Moskal and Zheng 2012) ecosystem studies (Lefsky et al. 2002) and stand value estimates (Murphy 2008). The demand on State and Federal agencies to manage large amounts of public land with limited resources is leading to increased reliance on advanced sensing technologies. The University of Washington and BLM studied Red Tree Vole Habitat in southern Oregon in the summer of 2012 to assess:
-How can survey grade GPS be used to accurately acquire individual tree location from aerial lidar data?
-To what extent do ground based inventories and leaf area measurements inform a lidar-driven habitat model?
Figure 1: Ground Based Inventories of Red Tree Vole Habitat. The images to the left show University of Washington students collecting data at habitat plots in southern Oregon. Crews acquired sub-centimeter GPS position accuracy for trees supporting vole nests with Dual-Frequency receivers. The research team also collected information at each plot, including species, DBH, height, height to live crown, and leaf area. The traditional ground methods of data acquisition help inform lidar-driven models and allow for a comparison with forest inventory methods using aerial lidar.
Red Tree Vole Plot
Red Tree Voles inhabit conifer forests,
and feed on conifer needles. The
scientific information needed to manage
the species cannot be derived solely from pre-project surveys (Red Tree Vole
Management Recommendations Version
2.0, BLM).
Project Area: Rogue River, OR
Figure 2: Red Tree Vole Nests Identified in the Lidar Project Area. The BLM has identified over 4,000 Red Tree Vole nests in the project area. The University of Washington collected survey grade GPS , leaf area measurements, and stem maps at 122 Red Tree Vole Nests throughout the project area in An extrapolative habitat model may prove important in managing Red Tree Vole habitat in the future.
Figure 3: Plot Level Aerial Lidar Images McMinnville, OR
Figure 4: Public Land Managed by BLM. The map on the left displays the large amount of land managed by the BLM. The BLM and Forest Service must ensure that any project in their jurisdiction does not contribute to the listing of a sensitive species as endangered. The two agencies must pay additional attention to rare or little known species thought to be associated with late-successional and old growth forests within the range of the Northern Spotted Owl. Research indicates that Oregon Red Tree Voles are more abundant in older forest conditions when compared to younger stands (Gillesberg and Carey 1991; Huff et al. 1992; Gomez 1992; Zentner1977). The listing of the North Oregon Coast population of Red Tree Voles as a candidate species by the U.S. Fish and Wildlife Department in October, 2011 manifests the salience of obtaining a lidar-driven habitat model for Red Tree Voles. The ability to utilize satellite and remotely sensed data , and to calibrate aerial lidar with GPS (Zhang and Moskal 2009; Moskal et al, 2009; Zhang and Moskal 2011), will provide a foundation for better understanding Red Tree Vole habitat.
THE ISSUE: The demand on public agencies to manage extensive forested land areas with limited resources requires more efficient inventory techniques. Survey grade GPS and traditional plot inventories can calibrate other remote sensing approaches and improve long term management strategies.
THE KEY QUESTIONS:
Can survey grade GPS be used to
accurately acquire individual
tree location from lidar data?
ⓒ RSGAL 2012
Citation: Author A, Author B, etc., YEAR. Title Goes Here. Factsheet # ?. Remote Sensing and Geospatial Application Laboratory, University of Washington, Seattle, WA. Digital version of the fact sheet can be downloaded at: