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You searched for subject:(radar ornithology). Showing records 1 – 2 of 2 total matches.

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University of Oklahoma

1. Horton, Kyle. USING RADAR TO REVEAL LARGE-SCALE IN-FLIGHT BEHAVIORS OF MIGRATORY BIRDS.

Degree: PhD, 2017, University of Oklahoma

The shortest possible migratory route for birds is not always the best route to travel. Substantial research effort has established that birds in captivity are capable of orienting toward the direction of an intended goal, but efforts to examine how free-living birds use navigational information under conditions that potentially make direct flight toward that goal inefficient have been limited in spatiotemporal scales and in the number of individuals observed because of logistical and technological limitations. Using novel and recently developed techniques for analysis of Doppler polarimetric weather surveillance radar data, I examine in-flight behaviors employed by migratory birds as they transition to and from their wintering and breeding grounds. I explore regional, seasonal, altitudinal, and latitudinal dependencies on how migrants utilize and cope with winds aloft. Advisors/Committee Members: Jeffrey, Kelly (advisor), Michael, Patten (committee member), Phillip, Chilson (committee member), Jeffrey, Buler (committee member), Eli, Bridge (committee member).

Subjects/Keywords: aeroecology; bird migration; radar ornithology; wind drift

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Horton, K. (2017). USING RADAR TO REVEAL LARGE-SCALE IN-FLIGHT BEHAVIORS OF MIGRATORY BIRDS. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/50744

Chicago Manual of Style (16th Edition):

Horton, Kyle. “USING RADAR TO REVEAL LARGE-SCALE IN-FLIGHT BEHAVIORS OF MIGRATORY BIRDS.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed June 23, 2018. http://hdl.handle.net/11244/50744.

MLA Handbook (7th Edition):

Horton, Kyle. “USING RADAR TO REVEAL LARGE-SCALE IN-FLIGHT BEHAVIORS OF MIGRATORY BIRDS.” 2017. Web. 23 Jun 2018.

Vancouver:

Horton K. USING RADAR TO REVEAL LARGE-SCALE IN-FLIGHT BEHAVIORS OF MIGRATORY BIRDS. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2018 Jun 23]. Available from: http://hdl.handle.net/11244/50744.

Council of Science Editors:

Horton K. USING RADAR TO REVEAL LARGE-SCALE IN-FLIGHT BEHAVIORS OF MIGRATORY BIRDS. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/50744


Montana State University

2. Mead, Reginald Marshall. A system for automating identification of biological echoes in NEXRAD level II radar data.

Degree: College of Engineering, 2009, Montana State University

Since its inception in the mid twentieth century, radar ornithology has provided scientists with new tools for studying the behavior of birds, especially with regards to migration. A number of studies have shown that birds can be detected using a wide variety of radar devices. Generally, these studies have focused on small portable radars that typically have a finer resolution than large weather surveillance radars. Recently, however, a number of researchers have presented qualitative evidence suggesting that birds, or at least migration events, can be identified using large broad scale radars such as the WSR-88D used in the NEXRAD weather surveillance system. This is potentially a boon for ornithologists because NEXRAD data covers a large portion of the country, is constantly being produced, is freely available, and is archived back into the early 1990s. A major obstacle is that identifying birds in NEXRAD data currently requires having a trained technician manually inspect a graphically rendered radar sweep. The immense amount of available data makes manual classification of radar echoes infeasible over any practical span of space or time. In this thesis, a system is presented for automating this process using machine learning techniques. This approach begins with classified training data that has been interpreted by experts or collected from direct observations. The data is preprocessed to ensure quality and to emphasize relevant features. A classifier is then trained using this data and cross validation is used to measure performance. The experiments in this thesis compare neural network, naïve Bayes, and k-nearest neighbor classifiers. Empirical evidence is provided showing that this system can achieve classification accuracies in the 80th to 90th percentile. Advisors/Committee Members: Chairperson, Graduate Committee: John Paxton. (advisor).

Subjects/Keywords: Artificial intelligence Computer programs.; Radar in ornithology.; Birds Migration.; Radar meteorology.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mead, R. M. (2009). A system for automating identification of biological echoes in NEXRAD level II radar data. (Thesis). Montana State University. Retrieved from http://scholarworks.montana.edu/xmlui/handle/1/1848

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mead, Reginald Marshall. “A system for automating identification of biological echoes in NEXRAD level II radar data.” 2009. Thesis, Montana State University. Accessed June 23, 2018. http://scholarworks.montana.edu/xmlui/handle/1/1848.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mead, Reginald Marshall. “A system for automating identification of biological echoes in NEXRAD level II radar data.” 2009. Web. 23 Jun 2018.

Vancouver:

Mead RM. A system for automating identification of biological echoes in NEXRAD level II radar data. [Internet] [Thesis]. Montana State University; 2009. [cited 2018 Jun 23]. Available from: http://scholarworks.montana.edu/xmlui/handle/1/1848.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mead RM. A system for automating identification of biological echoes in NEXRAD level II radar data. [Thesis]. Montana State University; 2009. Available from: http://scholarworks.montana.edu/xmlui/handle/1/1848

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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