Screening Global Positioning System Location Data for Errors Using Animal Movement Characteristics
Animal locations estimated by Global Positioning System (GPS) inherently contain errors. Screening procedures used to remove large positional errors often trade data accuracy for data loss. We developed a simple screening method that identifies locations arising from unrealistic movement patterns. W...
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| Published in | The Journal of wildlife management Vol. 74; no. 6; pp. 1361 - 1366 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
5410 Grosvenor Lane, Suite 200, Bethesda, MD 20814-2144
The Wildlife Society
01.08.2010
Blackwell Publishing Ltd |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Animal locations estimated by Global Positioning System (GPS) inherently contain errors. Screening procedures used to remove large positional errors often trade data accuracy for data loss. We developed a simple screening method that identifies locations arising from unrealistic movement patterns. When applied to a large data set of moose (Alces alces) locations, our method identified virtually all known errors with minimal loss of data. Thus, our method for screening GPS data improves the quality of data sets and increases the value of such data for research and management. |
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| AbstractList | Animal locations estimated by Global Positioning System (GPS) inherently contain errors. Screening procedures used to remove large positional errors often trade data accuracy for data loss. We developed a simple screening method that identifies locations arising from unrealistic movement patterns. When applied to a large data set of moose (Alces alces) locations, our method identified virtually all known errors with minimal loss of data. Thus, our method for screening GPS data improves the quality of data sets and increases the value of such data for research and management. Animal locations estimated by Global Positioning System (GPS) inherently contain errors. Screening procedures used to remove large positional errors often trade data accuracy for data loss. We developed a simple screening method that identifies locations arising from unrealistic movement patterns. When applied to a large data set of moose (Alces alces) locations, our method identified virtually all known errors with minimal loss of data. Thus, our method for screening GPS data improves the quality of data sets and increases the value of such data for research and management. [PUBLICATION ABSTRACT] |
| Author | Van Moorter, Bram Rolandsen, Christer Moe Bjørneraas, Kari Herfindal, Ivar |
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| Copyright | The Wildlife Society The Wildlife Society, 2010 Copyright Allen Press Publishing Services Aug 2010 |
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| SubjectTerms | Accuracy Alces alces Animals Artificial satellites Behavior Data processing data screening Datasets Ecological modeling Estimates Geometry Global Positioning System Global positioning systems GPS location accuracy location error Methods Moose movement behavior Navigation satellites Norway positional dilution of precision TOOLS AND TECHNOLOGY Wildlife Wildlife ecology Wildlife habitats Wildlife management |
| Title | Screening Global Positioning System Location Data for Errors Using Animal Movement Characteristics |
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