Literature DB >> 24973611

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring.

Jeffrey K Gillan1, Jason W Karl2, Michael Duniway3, Ahmed Elaksher4.   

Abstract

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, 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. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. 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 (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. 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.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Keywords:  Digital terrain model; Photogrammetry; Rangeland monitoring; Remote sensing; Vegetation height

Mesh:

Year:  2014        PMID: 24973611     DOI: 10.1016/j.jenvman.2014.05.028

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  4 in total

1.  Integrating drone imagery with existing rangeland monitoring programs.

Authors:  Jeffrey K Gillan; Jason W Karl; Willem J D van Leeuwen
Journal:  Environ Monit Assess       Date:  2020-04-06       Impact factor: 2.513

2.  Comparison of Remote Sensing Methods for Plant Heights in Agricultural Fields Using Unmanned Aerial Vehicle-Based Structure From Motion.

Authors:  Ryo Fujiwara; Tomohiro Kikawada; Hisashi Sato; Yukio Akiyama
Journal:  Front Plant Sci       Date:  2022-06-24       Impact factor: 6.627

3.  Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar.

Authors:  Dongliang Wang; Xiaoping Xin; Quanqin Shao; Matthew Brolly; Zhiliang Zhu; Jin Chen
Journal:  Sensors (Basel)       Date:  2017-01-19       Impact factor: 3.576

4.  Effective ecosystem monitoring requires a multi-scaled approach.

Authors:  Ben D Sparrow; Will Edwards; Samantha E M Munroe; Glenda M Wardle; Greg R Guerin; Jean-Francois Bastin; Beryl Morris; Rebekah Christensen; Stuart Phinn; Andrew J Lowe
Journal:  Biol Rev Camb Philos Soc       Date:  2020-07-09
  4 in total

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