Statistics of locations in tracks.
Characteristic of the locations within tracks obtained by first assigning detections to locations within tracks using one localization method and then using the other method to obtain the final locations. These plots are for a minimum probability of master detections and all detections of 0.9 and 0....
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ftsmithonian:oai:figshare.com:article/17207631 2023-05-15T15:36:24+02:00 Statistics of locations in tracks. William S. D. Wilcock (3749737) Rose S. Hilmo (4537330) 2021-12-15T18:23:25Z https://doi.org/10.1371/journal.pone.0260273.g013 unknown https://figshare.com/articles/figure/Statistics_of_locations_in_tracks_/17207631 doi:10.1371/journal.pone.0260273.g013 CC BY 4.0 CC-BY Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified studying marine mammals passive acoustic monitoring ocean bottom seismometers many spurious solutions increasing sampling rates future experiments might div >< p balaenoptera musculus </ widely spaced network false positives must obtain tracks using least 20 locations earliest arrival time different b calls true positives large network b call vocalize extensively smooth paths seismic frequencies requiring groups pacific northwest obtained iteratively minimize changes localize calls including constraints important tool follow within first harmonic feasible time distance window detecting harmonics describe methods calls identified approaches lead 15 hz Image Figure 2021 ftsmithonian https://doi.org/10.1371/journal.pone.0260273.g013 2021-12-19T19:26:38Z Characteristic of the locations within tracks obtained by first assigning detections to locations within tracks using one localization method and then using the other method to obtain the final locations. These plots are for a minimum probability of master detections and all detections of 0.9 and 0.2, respectively but the plots have similar characteristics for tracks obtained with all the choices of minimum probabilities listed in Table 3 . (a) Histogram of the travel time misfits normalized to the assumed uncertainties ( Table 1 ) for master detections (dark shading) and all detections (light shading) for locations in tracks with ≥ 20 locations with the final locations obtained using localization method 1 ( Eq 3 ). A solid line shows a Gaussian distribution fit to the histogram which has a standard deviation of 0.96. (b) As for (a) except the final locations are obtained with localization method 2 ( Eq 6 ). The Gaussian distribution fit to the histogram has a standard deviation of 1.35. (c) Histogram of the smallest horizontal 1-σ location error for all tracked locations (light shading) and tracks with ≥20 locations (dark shading) for final locations obtained with localization method 1. (d) As for (c) but for the largest horizontal location error. Still Image Balaenoptera musculus Unknown Pacific |
institution |
Open Polar |
collection |
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op_collection_id |
ftsmithonian |
language |
unknown |
topic |
Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified studying marine mammals passive acoustic monitoring ocean bottom seismometers many spurious solutions increasing sampling rates future experiments might div >< p balaenoptera musculus </ widely spaced network false positives must obtain tracks using least 20 locations earliest arrival time different b calls true positives large network b call vocalize extensively smooth paths seismic frequencies requiring groups pacific northwest obtained iteratively minimize changes localize calls including constraints important tool follow within first harmonic feasible time distance window detecting harmonics describe methods calls identified approaches lead 15 hz |
spellingShingle |
Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified studying marine mammals passive acoustic monitoring ocean bottom seismometers many spurious solutions increasing sampling rates future experiments might div >< p balaenoptera musculus </ widely spaced network false positives must obtain tracks using least 20 locations earliest arrival time different b calls true positives large network b call vocalize extensively smooth paths seismic frequencies requiring groups pacific northwest obtained iteratively minimize changes localize calls including constraints important tool follow within first harmonic feasible time distance window detecting harmonics describe methods calls identified approaches lead 15 hz William S. D. Wilcock (3749737) Rose S. Hilmo (4537330) Statistics of locations in tracks. |
topic_facet |
Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Physical Sciences not elsewhere classified studying marine mammals passive acoustic monitoring ocean bottom seismometers many spurious solutions increasing sampling rates future experiments might div >< p balaenoptera musculus </ widely spaced network false positives must obtain tracks using least 20 locations earliest arrival time different b calls true positives large network b call vocalize extensively smooth paths seismic frequencies requiring groups pacific northwest obtained iteratively minimize changes localize calls including constraints important tool follow within first harmonic feasible time distance window detecting harmonics describe methods calls identified approaches lead 15 hz |
description |
Characteristic of the locations within tracks obtained by first assigning detections to locations within tracks using one localization method and then using the other method to obtain the final locations. These plots are for a minimum probability of master detections and all detections of 0.9 and 0.2, respectively but the plots have similar characteristics for tracks obtained with all the choices of minimum probabilities listed in Table 3 . (a) Histogram of the travel time misfits normalized to the assumed uncertainties ( Table 1 ) for master detections (dark shading) and all detections (light shading) for locations in tracks with ≥ 20 locations with the final locations obtained using localization method 1 ( Eq 3 ). A solid line shows a Gaussian distribution fit to the histogram which has a standard deviation of 0.96. (b) As for (a) except the final locations are obtained with localization method 2 ( Eq 6 ). The Gaussian distribution fit to the histogram has a standard deviation of 1.35. (c) Histogram of the smallest horizontal 1-σ location error for all tracked locations (light shading) and tracks with ≥20 locations (dark shading) for final locations obtained with localization method 1. (d) As for (c) but for the largest horizontal location error. |
format |
Still Image |
author |
William S. D. Wilcock (3749737) Rose S. Hilmo (4537330) |
author_facet |
William S. D. Wilcock (3749737) Rose S. Hilmo (4537330) |
author_sort |
William S. D. Wilcock (3749737) |
title |
Statistics of locations in tracks. |
title_short |
Statistics of locations in tracks. |
title_full |
Statistics of locations in tracks. |
title_fullStr |
Statistics of locations in tracks. |
title_full_unstemmed |
Statistics of locations in tracks. |
title_sort |
statistics of locations in tracks. |
publishDate |
2021 |
url |
https://doi.org/10.1371/journal.pone.0260273.g013 |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
Balaenoptera musculus |
genre_facet |
Balaenoptera musculus |
op_relation |
https://figshare.com/articles/figure/Statistics_of_locations_in_tracks_/17207631 doi:10.1371/journal.pone.0260273.g013 |
op_rights |
CC BY 4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1371/journal.pone.0260273.g013 |
_version_ |
1766366757661966336 |