|Gillan, Jeffrey -|
|Duniway, Michael -|
|Elaksher, Ahmed -|
Submitted to: Journal of Environmental Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 25, 2014
Publication Date: June 1, 2014
Repository URL: http://handle.nal.usda.gov/10113/59328
Citation: Gillan, J., Karl, J.W., Duniway, M., Elaksher, A. 2014. Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring. Journal of Environmental Management. 144:226-235. Interpretive Summary: Height of vegetation and vertical vegetation structure (i.e., height variability) are important indicators of rangeland condition. Traditional field methods of measuring vegetation height are costly to apply across large landscapes. Emerging remote sensing techniques like LiDAR are also too expensive still to apply at these scales. However, an alternative remote sensing approach that is potentially more accessible to managers is to measure vegetation heights from digital stereo aerial photographs. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Digital surface models (5cm resolution) were created from overlapping HR aerial photographs of study plots near Lake Mead, NV. Height of shrubs from these images were compared to field data collected on the plots. On average, shrub height was underestimated by the stereo image analysis technique compared to the field measurements. Estimates of vertical structure will be more accurate in plots having low herbaceous cover and high amounts of dense shrubs. Our results illustrate the potential to derive vegetation height estimates quickly for large area using established remote-sensing techniques, and also point out the need for field vegetation measurements that better match heights estimated from remote-sensing methods.
Technical Abstract: Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for monitoring rangeland health or progress toward management objectives because of its importance for assessing riparian areas, post-fire recovery, wind erosion, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are also often too expensive, require specialized sensors, or are not of high enough resolution to meet monitoring objectives. An alternative remote sensing approach that is potentially more accessible to managers is to measure vegetation heights from digital stereo aerial photographs. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. Individual shrub heights were generally underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot height averages were also underestimated compared with the field measurements. Grasses and forbs in our plots were generally too small to be adequately modeled with the resolution of imagery we used. Estimates of vertical structure will be more accurate in plots having low herbaceous cover and high amounts of dense shrubs. Through the use of statistically derived correction factors or choosing field methods that better correlate with the imagery, vegetation heights from HR DSMs could be a valuable technique for broad-scale rangeland monitoring needs.