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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Investigating Nocturnal Uas Treatments In An Applied Context To Prevent Gulls From Nesting On Rooftops, Morgan Pfeiffer, Craig K. Pullins, Scott F. Beckerman, Joshua L. Hoblet, Brad Blackwell
Investigating Nocturnal Uas Treatments In An Applied Context To Prevent Gulls From Nesting On Rooftops, Morgan Pfeiffer, Craig K. Pullins, Scott F. Beckerman, Joshua L. Hoblet, Brad Blackwell
USDA Wildlife Services: Staff Publications
Ring‐billed (Larus delawarensis) and herring (L. argentatus) gulls are numerous and widespread in North America. These gulls rank among the top 9 species for risk of bird‐aircraft collisions (hereafter strikes). The ubiquitous presence of gulls in urban coastal environments, including rooftop nesting behavior, are factors impacting strike risk. Our purpose was to assess gull response to a small uncrewed aircraft system (UAS) in hazing flights at night during the nest‐building phase. We hypothesized that nocturnal UAS operation, like nocturnal predator disturbance, might reduce gull numbers and, thus, strike risk to aircraft. In spring 2021, we conducted …
Improving Animal Monitoring Using Small Unmanned Aircraft Systems (Suas) And Deep Learning Networks, Meilun Zhou, Jared A. Elmore, Sathishkumar Samiappan, Kristine O. Evans, Morgan Pfeiffer, Bradley F. Blackwell, Raymond B. Iglay
Improving Animal Monitoring Using Small Unmanned Aircraft Systems (Suas) And Deep Learning Networks, Meilun Zhou, Jared A. Elmore, Sathishkumar Samiappan, Kristine O. Evans, Morgan Pfeiffer, Bradley F. Blackwell, Raymond B. Iglay
USDA Wildlife Services: Staff Publications
In recent years, small unmanned aircraft systems (sUAS) have been used widely to monitor animals because of their customizability, ease of operating, ability to access difficult to navigate places, and potential to minimize disturbance to animals. Automatic identification and classification of animals through images acquired using a sUAS may solve critical problems such as monitoring large areas with high vehicle traffic for animals to prevent collisions, such as animal-aircraft collisions on airports. In this research we demonstrate automated identification of four animal species using deep learning animal classification models trained on sUAS collected images. We used a sUAS mounted with …
Evidence On The Effectiveness Of Small Unmanned Aircraft Systems (Suas) As A Survey Tool For North American Terrestrial, Vertebrate Animals: A Systematic Map Protocol, Jared A. Elmore, Michael F. Curran, Kristine O. Evans, Sathishkumar Samiappan, Meilun Zhou, Morgan B. Pfeiffer, Bradley F. Blackwell, Raymond B. Iglay
Evidence On The Effectiveness Of Small Unmanned Aircraft Systems (Suas) As A Survey Tool For North American Terrestrial, Vertebrate Animals: A Systematic Map Protocol, Jared A. Elmore, Michael F. Curran, Kristine O. Evans, Sathishkumar Samiappan, Meilun Zhou, Morgan B. Pfeiffer, Bradley F. Blackwell, Raymond B. Iglay
USDA Wildlife Services: Staff Publications
Background: Small unmanned aircraft systems (sUAS) are replacing or supplementing manned aircraft and groundbased surveys in many animal monitoring situations due to better coverage at finer spatial and temporal resolutions, access, cost, bias, impacts, safety, efficiency, and logistical benefits. Various sUAS models and sensors are available with varying features and usefulness depending on survey goals. However, justification for selection of sUAS and sensors are not typically offered in published literature and existing reviews do not adequately cover past and current sUAS applications for animal monitoring nor their associated sUAS model and sensor technologies, taxonomic and geographic scope, flight conditions and …
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 …