Research Article: Using Unmanned Aerial Vehicles for Rangelands: Current Applications and Future Potentials

Abstract

H igh resolution aerial photographs have important rangeland applications, such as monitoring vegetation change, developing grazing management practices, determining rangeland health and condition, and assessing remediation treatment effectiveness (Rango and Havstad, 2003). Unmanned Aerial Vehicles (UAVs) have several advantages over piloted aircraft for acquiring high resolution images. These advantages include a less expensive remote sensing platform, improved safety for operators, and a more rapid deployment capability than piloted aircraft.Most applications of UAVs in rangeland areas, which make up 50% to 70% of the world's land surface (Holechek, Pieper, and Herbel, 1995), only require simple high resolution photography and thermal infrared imagery that can be provided with existing sensors over selected sites. Unmanned Aerial Vehicle flight requirements over rangeland are also simple, with slow flight speeds, low altitudes, and flight durations of two to six hours usually being adequate. Such capabilities should be sufficient to satisfy the need for high resolution photography of remote rangeland areas. Satellite and piloted aircraft missions (both high and low altitudes) have provided excellent data for rangeland applications, but a major gap exists between these large area coverages and boom-mounted vertical ground photography of small areas; UAVs can fill this gap. Because the large area coverage can provide landscape level views, high resolution satellite data can be used to identify rangeland areas (in the case of rangeland health assessments) that need more detailed observations; UAVs then can be uti-

Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring

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Remote Sensing of Vegetation Structure Using Computer Vision

“…Inexpensive hobbyist aircraft (IHA), including radio-controlled fixed wing airplanes, helicopters, balloons and kites, are increasingly being used for low-altitude aerial photography (≤120 m) in part because it has become a simple matter to deploy consumer-grade digital cameras on these platforms [14][15][16]. It has also become relatively simple to generate 3D geometry from sets of overlapping digital photographs acquired using uncalibrated consumer-grade cameras using newly-developed computer vision algorithms that completely automate this process using Structure from Motion procedures (SfM) [17].…”

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