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RESEARCH ARTICLE: Using Unmanned Aerial Vehicles for Rangelands: Current Applications and Future Potentials

Published online by Cambridge University Press:  25 October 2006

Albert Rango
Affiliation:
USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, New Mexico
Andrea Laliberte
Affiliation:
USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, New Mexico
Caiti Steele
Affiliation:
USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, New Mexico
Jeffrey E. Herrick
Affiliation:
USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, New Mexico
Brandon Bestelmeyer
Affiliation:
USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, New Mexico
Thomas Schmugge
Affiliation:
College of Agriculture, New Mexico State University, Las Cruces, New Mexico
Abigail Roanhorse
Affiliation:
Department of Agriculture and Biosystems Engineering, University of Arizona, Tucson, Arizona
Vince Jenkins
Affiliation:
Securaplane Technologies, Inc., Tucson, Arizona
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Abstract

High resolution aerial photographs have important rangeland applications, such as monitoring vegetation change, developing grazing strategies, determining rangeland health, and assessing remediation treatment effectiveness. Acquisition of high resolution images by Unmanned Aerial Vehicles (UAVs) has certain advantages over piloted aircraft missions, including lower cost, improved safety, flexibility in mission planning, and closer proximity to the target. Different levels of remote sensing data can be combined to provide more comprehensive information: 15–30 m resolution imaging from space-borne sensors for determining uniform landscape units; < 1 m satellite or aircraft data to assess the pattern of ecological states in an area of interest; 5 cm UAV images to measure gap and patch sizes as well as percent bare soil and vegetation ground cover; and < 1 cm ground-based boom photography for ground truth or reference data. Two parallel tracks of investigation are necessary: one that emphasizes the utilization of the most technically advanced sensors for research, and a second that emphasizes the minimization of costs and the maximization of simplicity for monitoring purposes. We envision that in the future, resource management agencies, rangeland consultants, and private land managers should be able to use small, lightweight UAVs to satisfy their needs for acquiring improved data at a reasonable cost, and for making appropriate management decisions.

Type
FEATURES & REVIEWS
Copyright
© 2006 National Association of Environmental Professionals

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References

REFERENCES

Bestelmeyer, G. T., J. E. Herrick, J. R. Brown, D. A. Trujillo, and K. M. Havstad. 2004. Land Management in the American Southwest: A State-and-Transition Approach to Ecosystem Complexity. Environmental Management 34:3851.Google Scholar
Definiens. 2003. Definiens Imaging, eCognition. http://www.definiens.com. Accessed October 25, 2005.
Hardin, P. J., and M. W. Jackson. 2005. An Unmanned Aerial Vehicle for Rangeland Photography. Rangeland Ecology & Management 58:439442.Google Scholar
Havstad, K. M., W. P. Kustas, A. Rango, J. R. Ritchie, and T. J. Schmugge. 2000. Jornada Experimental Range: A Unique Arid Land Location for Experiments to Validate Satellite Systems and to Understand Effects of Climate. Remote Sensing of Environment 74(1):1325.Google Scholar
Herrick, J. E., J. W. Van Zee, K. M. Havstad, L. M. Burkett, and W. G. Whitford. 2005. Monitoring Manual for Grassland, Shrubland and Savanna Ecosystems. Volume I: Quick Start and Volume II: Design, Supplementary Methods and Interpretation. USDA-ARS Jornada Experimental Range, Las Cruces, NM, 236 pp.
Holechek, J. L., R. D. Pieper, and C. H. Herbel. 1995. Rangeland Management: Principles and Practice. Prentice Hall, Upper Saddle River, NJ, 526 pp.
Holm, A. M., L. T. Bennett, W. A. Loneragan, and M. A. Adams. 2002. Relationships between Empirical and Nominal Indices of Landscape Function in the Arid Shrubland of Western Australia. Journal of Arid Environments 50(1):121.Google Scholar
Horcher, A., and R. J. M. Visser. 2004. Unmanned Aerial Vehicles: Application for Natural Resource Management and Monitoring. Proceedings of the Council of Forest Engineering Annual Meeting—Machines and People, The Interface, 5 pp.
Johnson, L. F., S. Herwitz, S. Dunagan, B. Lobitz, D. Sullivan, and R. Slye. 2003. Collection of Ultra High Spatial and Spectral Resolution Image Data over California Vineyards with Small UAV. Proceedings of the 30th International Symposium on Remote Sensing of Environment, Honolulu, HI, CD paper TS-12.4, 3 pp.
Laliberte, A. S., E. L. Fredrickson, and A. Rango. In press, 2006. Combining Decision Trees with Hierarchical Object-Oriented Image Analysis for Mapping Rangelands. Engineering and Remote Sensing.Google Scholar
Laliberte, A. S., A. Rango, K. M. Havstad, J. F. Paris, R. F. Beck. R. McNeely, and A. L. Gonzalez. 2004. Object-Oriented Image Analysis for Mapping Shrub Encroachment from 1937 to 2003 in Southern New Mexico. Remote Sensing of Environment 93:198210.Google Scholar
Ludwig, J. A., G. N. Bastin, W. R. Eager, R. Karfs, P. Ketner, and G. Pearce. 2000. Monitoring Australian Rangeland Sites Using Landscape Function Indicators and Ground- and Remote-Based Techniques. Environmental Monitoring and Assessment 64:167178.Google Scholar
MLB Company. 2006. MLB Company Web site. http://www.spyplanes.com/index.html. Accessed June 2006.
NASA. 2005. UAVs for Land Management and Coastal Zone Dynamics Workshop, July 26–27. http://innovationlabs.com/uav5/UAV_Land-Ocean_summary.pdf. Accessed October 25, 2005.
Newcome, L. R. 2004. Unmanned Aviation: A Brief History of Unmanned Aerial Vehicles, 1st Edition. American Institute of Aeronautics and Astronautics, Inc., Reston, VA, 172 pp.
Privette, J. L., G. P. Asner, J. Conel, K. F. Huemmrich, R. Olson, A. Rango, A. F. Rahman, K. Thome, and E. A. Walter-Shea. 2000. The EOS Prototype Validation Exercise (PROVE) at Jornada: Overview and Lessons Learned. Remote Sensing of Environment 74(1):112.Google Scholar
Quilter, M. C., and V. J. Anderson. 2001. A Proposed Method for Determining Shrub Utilization Using (LA/LS) Imagery. Journal of Range Management 54:378381.Google Scholar
Rango, A., and K. Havstad. 2003. The Utility of Historical Aerial Photographs for Detecting and Judging the Effectiveness of Rangeland Remediation Treatments. Environmental Practice 5(2):107118.Google Scholar
Rango, A., L. Huenneke, M. Buonopane, J. E. Herrick, and K. M. Havstad. 2005. Using Historic Data to Assess Effectiveness of Shrub Removal in Southern New Mexico. Journal of Arid Environments 62:7591.Google Scholar
Rango, A., J. C. Ritchie, W. P. Kustas, T. J. Schmugge, and K. M. Havstad. 1998. JORNEX: Remote Sensing to Quantify Long-Term Vegetation Change and Hydrological Fluxes in an Arid Rangeland Environment. In Hydrology in a Changing Environment, Volume II, British Hydrological Society, Exeter, UK, 133139.
Rango, A., S. L. Tartowski, A. Laliberte, J. Wainwright, and A. Parsons. 2006. Islands of Hydrologically Enhanced Biotic Productivity in Natural and Managed Arid Ecosystems. Journal of Arid Environments 65(2):235252.Google Scholar
US Forest Service. 2005. Unpublished data.
Veisze, P. M. 1997. Low and Slow—Development of Remote Piloted Vehicles for Small Systems Remote Sensing Research. http://www.rsr.org/veisze_low_and_slow.html. 4 pp. Accessed October 25, 2005.
Walker, J. W. 1993. Low Altitude Large Scale Reconnaissance: A Method of Obtaining High Resolution Vertical Photographs for Small Areas. Interagency Archeological Services, National Park Service, Denver, CO, 127 pp.
Winter, M., D. H. Johnson, J. A. Shaffer, T. M. Donovan, and W. D. Sverdarsky. 2006. Patch Size and Landscape Effects on Density and Nesting Success of Grassland Birds. Journal of Wildlife Management 70(1):158172.Google Scholar