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Screening Global Positioning System Location Data for Errors Using Animal Movement Characteristics
Author(s) -
BJØRNERAAS KARI,
MOORTER BRAM,
ROLANDSEN CHRISTER MOE,
HERFINDAL IVAR
Publication year - 2010
Publication title -
the journal of wildlife management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 111
eISSN - 1937-2817
pISSN - 0022-541X
DOI - 10.1111/j.1937-2817.2010.tb01258.x
Subject(s) - global positioning system , computer science , data set , set (abstract data type) , data quality , location data , data mining , simple (philosophy) , movement (music) , artificial intelligence , real time computing , engineering , telecommunications , metric (unit) , philosophy , operations management , programming language , aesthetics , epistemology
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.