1 August 2009 Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management
Albert Rango, Andrea Laliberte, Jeffrey E. Herrick, Craig Winters, Kris Havstad, Caiti Steele, Dawn Browning
Author Affiliations +
Abstract
Rangeland comprises as much as 70% of the Earth's land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satellites and piloted aircraft: they can be deployed quickly and repeatedly; they are less costly and safer than piloted aircraft; they are flexible in terms of flying height and timing of missions; and they can obtain imagery at sub-decimeter resolution. This hyperspatial imagery allows for quantification of plant cover, composition, and structure at multiple spatial scales. Our experiments have shown that this capability, from an off-the-shelf mini-UAV, is directly applicable to operational agency needs for measuring and monitoring. For use by operational agencies to carry out their mandated responsibilities, various requirements must be met: an affordable and reliable platform; a capability for autonomous, low altitude flights; takeoff and landing in small areas surrounded by rugged terrain; and an easily applied data analysis methodology. A number of image processing and orthorectification challenges have been or are currently being addressed, but the potential to depict the land surface commensurate with field data perspectives across broader spatial extents is unrivaled.
Albert Rango, Andrea Laliberte, Jeffrey E. Herrick, Craig Winters, Kris Havstad, Caiti Steele, and Dawn Browning "Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management," Journal of Applied Remote Sensing 3(1), 033542 (1 August 2009). https://doi.org/10.1117/1.3216822
Published: 1 August 2009
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CITATIONS
Cited by 264 scholarly publications.
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KEYWORDS
Unmanned aerial vehicles

Remote sensing

Image resolution

Photography

Satellites

Vegetation

Image processing

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