Efficient 3D movement-based kernel density estimator and application to wildlife ecology
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Abstract
We describe an efficient implementation of a 3D movement-based kernel density estimator for determining animal space use from discrete GPS measurements. This new method provides more accurate results, particularly for species that make large excursions in the vertical dimension. The downside of this approach is that it is much more computationally expensive than simpler, lower-dimensional models. Through a combination of code restructuring, parallelization and performance optimization, we were able to reduce the time to solution by up to a factor of 1000x, thereby greatly improving the applicability of the method.
Publication type | Conference Paper |
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Publication Subtype | Conference Paper |
Title | Efficient 3D movement-based kernel density estimator and application to wildlife ecology |
DOI | 10.1145/2616498.2616522 |
Year Published | 2014 |
Language | English |
Publisher | ACM |
Contributing office(s) | Western Ecological Research Center |
Description | art14 |
Larger Work Type | Conference Paper |
Larger Work Subtype | Conference Paper |
Larger Work Title | Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment |
Conference Title | 2014 Annual Conference on Extreme Science and Engineering Discovery Environment |
Conference Location | Atlanta, GA |
Conference Date | July 13-18, 2014 |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |