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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Estimating Waterbird Abundance On Catfish Aquaculture Ponds Using An Unmanned Aerial System, Paul C. Burr, Sathishkumar Samiappan, Lee A. Hathcock, Robert J. Moorhead, Brian S. Dorr
Estimating Waterbird Abundance On Catfish Aquaculture Ponds Using An Unmanned Aerial System, Paul C. Burr, Sathishkumar Samiappan, Lee A. Hathcock, Robert J. Moorhead, Brian S. Dorr
USDA Wildlife Services: Staff Publications
In this study, we examined the use of an unmanned aerial system (UAS) to monitor fish-eating birds on catfish (Ictalurus spp.) aquaculture facilities in Mississippi, USA. We tested 2 automated computer algorithms to identify bird species using mosaicked imagery taken from a UAS platform. One algorithm identified birds based on color alone (color segmentation), and the other algorithm used shape recognition (template matching), and the results of each algorithm were compared directly to manual counts of the same imagery. We captured digital imagery of great egrets (Ardea alba), great blue herons (A. herodias), and doublecrested cormorants (Phalacrocorax auritus) on aquaculture …
Use Of Unmanned Aircraft Systems (Uas) And Multispectral Imagery For Quantifying Agricultural Areas Damaged By Wild Pigs, Justin W. Fischer, Kelsey Greiner, Mark W. Lutman, Bryson L. Webber, Kurt C. Vercauteren
Use Of Unmanned Aircraft Systems (Uas) And Multispectral Imagery For Quantifying Agricultural Areas Damaged By Wild Pigs, Justin W. Fischer, Kelsey Greiner, Mark W. Lutman, Bryson L. Webber, Kurt C. Vercauteren
USDA Wildlife Services: Staff Publications
Wild pigs (Sus scrofa) cause extensive damage to agricultural crops, resulting in lost production and income. A major challenge associated with assessing damage to crops is locating and quantifying damaged areas within agricultural fields. We evaluated a novel method using multispectral high-resolution aerial imagery, collected from sensors mounted on unmanned aircraft systems (UAS), and feature extraction techniques to detect and map areas of corn fields damaged by wild pigs in southern Missouri, USA. Damaged areas were extracted from orthomosaics using visible and near-infrared band combinations, an object-based classification approach, and hierarchical learning cycles. To validate estimates we also collected ground …