Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning
A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with unce...
Uloženo v:
| Vydáno v: | PloS one Ročník 11; číslo 7; s. e0158248 |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
Public Library of Science
01.07.2016
Public Library of Science (PLoS) |
| Témata: | |
| ISSN: | 1932-6203, 1932-6203 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS) are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM) using vessel speed as observation variable. For longliners we have designed a Data Mining (DM) approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public. |
|---|---|
| AbstractList | A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS) are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011–2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM) using vessel speed as observation variable. For longliners we have designed a Data Mining (DM) approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public. A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS) are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM) using vessel speed as observation variable. For longliners we have designed a Data Mining (DM) approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public.A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS) are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM) using vessel speed as observation variable. For longliners we have designed a Data Mining (DM) approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public. |
| Audience | Academic |
| Author | de Souza, Erico N. Boerder, Kristina Matwin, Stan Worm, Boris |
| AuthorAffiliation | 2 Biology Department, Dalhousie University, Halifax, NS, Canada 3 Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland 1 Big Data Analytics Institute, Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada Aristotle University of Thessaloniki, GREECE |
| AuthorAffiliation_xml | – name: Aristotle University of Thessaloniki, GREECE – name: 1 Big Data Analytics Institute, Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada – name: 2 Biology Department, Dalhousie University, Halifax, NS, Canada – name: 3 Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland |
| Author_xml | – sequence: 1 givenname: Erico N. surname: de Souza fullname: de Souza, Erico N. – sequence: 2 givenname: Kristina surname: Boerder fullname: Boerder, Kristina – sequence: 3 givenname: Stan surname: Matwin fullname: Matwin, Stan – sequence: 4 givenname: Boris surname: Worm fullname: Worm, Boris |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27367425$$D View this record in MEDLINE/PubMed |
| BookMark | eNqNk2tr1EAUhoNU7EX_gWhAEP2w69xy84OwtFYXtlRc6zcZTiaT3VmSmXVmUvTfO-mmZVOKlEBmOHnOOyfvnHMcHWijZRS9xGiKaYY_bExnNTTTbQhPEU5ywvIn0REuKJmkBNGDvf1hdOzcBqGE5mn6LDokGU0zRpKj6Ne83VpzrfQqPldu3a_fwHtpdXwmvRReGR3X1rTxErxsGuVlPJsv4yvXo2fgIb5Qut-DruILEEFCxgsJtg8-j57W0Dj5YlhPoqvzzz9Ov04Wl1_mp7PFRGQk8ZNUpCXQVCQixbJkFZQVJigrcJHgQmCgNSrDW2R5kZQpphjyLCkYCESpLKCgJ9Hrne62MY4PzjiOc4QRSRnGgZjviMrAhm-tasH-5QYUvwkYu-JgvRKN5BShvBShHkqAFXUohua4IozWIksozYPWp-G0rmxlJaT2FpqR6PiLVmu-MtecFRQR3Au8GwSs-d1J53mrnAjugpamu6k7z0iR0UehmFFGEArom3vow0YM1ArCvypdm1Ci6EX5jCVpRos87bWmD1DhqWSrROi4WoX4KOH9KCEwXv7xK-ic4_Pl98ezlz_H7Ns9di2h8Wtnmq7vSzcGX-1fyt1t3LZ6ANgOENY4Z2V9h2DE-4m6tYv3E8WHiQppH--lCeWhPz44opr_J_8DIHckLg |
| CitedBy_id | crossref_primary_10_1016_j_marpol_2019_103675 crossref_primary_10_1109_ACCESS_2019_2945056 crossref_primary_10_1111_csp2_12926 crossref_primary_10_1007_s00773_019_00694_5 crossref_primary_10_1016_j_oneear_2022_08_006 crossref_primary_10_1016_j_fishres_2023_106793 crossref_primary_10_1016_j_jenvman_2023_119735 crossref_primary_10_1109_ACCESS_2020_2980322 crossref_primary_10_1016_j_marpol_2018_02_012 crossref_primary_10_1016_j_oceaneng_2023_116630 crossref_primary_10_1155_2022_2700674 crossref_primary_10_1016_j_tre_2025_104159 crossref_primary_10_1051_alr_2017038 crossref_primary_10_1007_s00227_021_03841_y crossref_primary_10_1109_ACCESS_2020_3022865 crossref_primary_10_3389_fmars_2021_635568 crossref_primary_10_1016_j_oneear_2024_09_009 crossref_primary_10_1007_s10707_020_00408_9 crossref_primary_10_1007_s10707_022_00463_4 crossref_primary_10_1038_s41598_018_36915_x crossref_primary_10_58930_bp42323989 crossref_primary_10_1080_1523908X_2018_1461084 crossref_primary_10_1126_sciadv_ads1592 crossref_primary_10_1016_j_ocecoaman_2022_106280 crossref_primary_10_1139_cjfas_2016_0446 crossref_primary_10_1371_journal_pone_0313197 crossref_primary_10_3389_fmars_2019_00537 crossref_primary_10_1007_s00343_022_2005_5 crossref_primary_10_1016_j_marpol_2019_103520 crossref_primary_10_1111_1365_2664_13849 crossref_primary_10_3389_fmars_2017_00409 crossref_primary_10_1038_s41598_025_88158_2 crossref_primary_10_1007_s12601_023_00126_x crossref_primary_10_1016_j_ecoinf_2022_101903 crossref_primary_10_1016_j_is_2025_102523 crossref_primary_10_1016_j_marpol_2017_12_013 crossref_primary_10_3389_fmars_2021_685808 crossref_primary_10_3389_fmars_2022_808282 crossref_primary_10_1086_708720 crossref_primary_10_3389_fmars_2025_1532964 crossref_primary_10_1111_exsy_12252 crossref_primary_10_3389_fmars_2023_1171641 crossref_primary_10_3389_fsufs_2023_1152226 crossref_primary_10_1371_journal_pone_0216819 crossref_primary_10_1016_j_atmosenv_2021_118382 crossref_primary_10_1016_j_ecolind_2023_110628 crossref_primary_10_1093_icesjms_fsae006 crossref_primary_10_1002_mcf2_10309 crossref_primary_10_1007_s10044_024_01263_2 crossref_primary_10_1017_S037346331800067X crossref_primary_10_1111_faf_12669 crossref_primary_10_1016_j_fishres_2021_105896 crossref_primary_10_1109_ACCESS_2021_3077514 crossref_primary_10_1016_j_ocecoaman_2023_106690 crossref_primary_10_1007_s12562_023_01734_1 crossref_primary_10_1038_s41467_022_28916_2 crossref_primary_10_1016_j_marpol_2019_02_038 crossref_primary_10_1007_s13437_018_0151_6 crossref_primary_10_1002_ece3_4176 crossref_primary_10_1371_journal_pone_0321116 crossref_primary_10_3233_JIFS_231447 crossref_primary_10_1111_faf_12596 crossref_primary_10_3389_fmars_2020_580612 crossref_primary_10_1002_aqc_4015 crossref_primary_10_1007_s00530_020_00733_x crossref_primary_10_1038_s44183_023_00023_9 crossref_primary_10_1080_09669582_2021_1887878 crossref_primary_10_1016_j_marpol_2018_11_006 crossref_primary_10_1038_s41558_024_02127_7 crossref_primary_10_1111_faf_12559 crossref_primary_10_3389_fmars_2022_1051879 crossref_primary_10_1177_25148486221111786 crossref_primary_10_1007_s11802_021_4518_5 crossref_primary_10_1139_cjfas_2023_0291 crossref_primary_10_1007_s11431_018_9335_1 crossref_primary_10_1016_j_fishres_2023_106614 crossref_primary_10_1126_science_aao5646 crossref_primary_10_1007_s11277_020_07200_w crossref_primary_10_1088_2053_1583_ab3771 crossref_primary_10_1139_cjfas_2023_0123 crossref_primary_10_1007_s13437_023_00312_7 crossref_primary_10_1371_journal_pone_0282374 crossref_primary_10_1371_journal_pone_0269490 crossref_primary_10_1007_s10707_019_00365_y crossref_primary_10_1016_j_oceaneng_2024_120136 crossref_primary_10_1016_j_ocecoaman_2022_106136 crossref_primary_10_1111_faf_12285 crossref_primary_10_1016_j_ecoinf_2021_101384 crossref_primary_10_1080_23308249_2021_1937044 crossref_primary_10_1007_s13437_021_00251_1 crossref_primary_10_1038_s41598_022_05142_w crossref_primary_10_1111_faf_12647 crossref_primary_10_1017_S0373463318000188 crossref_primary_10_1109_ACCESS_2024_3416389 |
| Cites_doi | 10.1093/icesjms/fsq137 10.1016/j.sigpro.2005.01.012 10.1126/science.1149345 10.1139/cjfas-2013-0552 10.2307/1941448 10.1126/science.aad5686 10.1093/icesjms/fsq010 10.1016/j.ecolmodel.2010.05.007 10.2307/3801959 10.1109/SDF.2015.7347707 10.1109/OCEANSE.2009.5278254 10.1109/SPSC.2008.4686715 10.1016/j.icesjms.2004.12.002 10.1136/bmj.309.6947.102 10.1017/S0373463305003267 10.1017/S037346331100066X 10.1139/f2011-055 10.1109/BigData.2014.7004281 10.1371/journal.pone.0130746 10.1016/S0304-4149(99)00023-X 10.1371/journal.pone.0082898 10.1093/icesjms/fss166 10.1016/j.ecolmodel.2006.03.017 10.18637/jss.v050.i09 10.1016/j.biocon.2011.02.024 10.2307/3800474 10.1890/0012-9658(2003)084[0282:UFPTIT]2.0.CO;2 10.1002/sat.957 10.1139/f2011-114 10.1139/cjfas-2013-0572 10.1016/j.ecolmodel.2010.04.005 10.1371/journal.pone.0001111 10.3390/e15062218 |
| ContentType | Journal Article |
| Copyright | COPYRIGHT 2016 Public Library of Science 2016 de Souza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2016 de Souza et al 2016 de Souza et al |
| Copyright_xml | – notice: COPYRIGHT 2016 Public Library of Science – notice: 2016 de Souza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2016 de Souza et al 2016 de Souza et al |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM IOV ISR 3V. 7QG 7QL 7QO 7RV 7SN 7SS 7T5 7TG 7TM 7U9 7X2 7X7 7XB 88E 8AO 8C1 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABJCF ABUWG AEUYN AFKRA ARAPS ATCPS AZQEC BBNVY BENPR BGLVJ BHPHI C1K CCPQU D1I DWQXO FR3 FYUFA GHDGH GNUQQ H94 HCIFZ K9. KB. KB0 KL. L6V LK8 M0K M0S M1P M7N M7P M7S NAPCQ P5Z P62 P64 PATMY PDBOC PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PTHSS PYCSY RC3 7X8 5PM DOA |
| DOI | 10.1371/journal.pone.0158248 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Gale In Context: Opposing Viewpoints Gale In Context: Science ProQuest Central (Corporate) Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts Nursing & Allied Health Database Ecology Abstracts Entomology Abstracts (Full archive) Immunology Abstracts Meteorological & Geoastrophysical Abstracts Nucleic Acids Abstracts Virology and AIDS Abstracts Agricultural Science Collection Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) ProQuest Pharma Collection Public Health Database Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection Agricultural & Environmental Science Collection ProQuest Central Essentials Biological Science Collection ProQuest Central ProQuest Technology Collection Natural Science Collection Environmental Sciences and Pollution Management ProQuest One ProQuest Materials Science Collection ProQuest Central Korea Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student AIDS and Cancer Research Abstracts SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Materials Science Database Nursing & Allied Health Database (Alumni Edition) Meteorological & Geoastrophysical Abstracts - Academic ProQuest Engineering Collection ProQuest Biological Science Collection Agricultural Science Database ProQuest Health & Medical Collection Medical Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Database Engineering Database Nursing & Allied Health Premium Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Environmental Science Database Materials Science Collection ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Engineering Collection Environmental Science Collection Genetics Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Agricultural Science Database Publicly Available Content Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials Nucleic Acids Abstracts SciTech Premium Collection ProQuest Central China Environmental Sciences and Pollution Management ProQuest One Applied & Life Sciences ProQuest One Sustainability Health Research Premium Collection Meteorological & Geoastrophysical Abstracts Natural Science Collection Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Engineering Collection Advanced Technologies & Aerospace Collection Engineering Database Virology and AIDS Abstracts ProQuest Biological Science Collection ProQuest One Academic Eastern Edition Agricultural Science Collection ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database Ecology Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Environmental Science Collection Entomology Abstracts Nursing & Allied Health Premium ProQuest Health & Medical Complete ProQuest One Academic UKI Edition Environmental Science Database ProQuest Nursing & Allied Health Source (Alumni) Engineering Research Database ProQuest One Academic Meteorological & Geoastrophysical Abstracts - Academic ProQuest One Academic (New) Technology Collection Technology Research Database ProQuest One Academic Middle East (New) Materials Science Collection ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central ProQuest Health & Medical Research Collection Genetics Abstracts ProQuest Engineering Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Agricultural & Environmental Science Collection AIDS and Cancer Research Abstracts Materials Science Database ProQuest Materials Science Collection ProQuest Public Health ProQuest Nursing & Allied Health Source ProQuest SciTech Collection Advanced Technologies & Aerospace Database ProQuest Medical Library Animal Behavior Abstracts Materials Science & Engineering Collection Immunology Abstracts ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic Agricultural Science Database MEDLINE Engineering Research Database |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: ProQuest Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Sciences (General) Ecology Computer Science |
| DocumentTitleAlternate | Identifying Fishing Activity from AIS |
| EISSN | 1932-6203 |
| ExternalDocumentID | 1801026411 oai_doaj_org_article_3008bca3632a49fabd381d243fc75338 PMC4930218 4106196861 A456739860 27367425 10_1371_journal_pone_0158248 |
| Genre | Journal Article |
| GeographicLocations | Poland Canada |
| GeographicLocations_xml | – name: Canada – name: Poland |
| GroupedDBID | --- 123 29O 2WC 53G 5VS 7RV 7X2 7X7 7XC 88E 8AO 8C1 8CJ 8FE 8FG 8FH 8FI 8FJ A8Z AAFWJ AAUCC AAWOE AAYXX ABDBF ABIVO ABJCF ABUWG ACCTH ACGFO ACIHN ACIWK ACPRK ACUHS ADBBV ADRAZ AEAQA AENEX AEUYN AFFHD AFKRA AFPKN AFRAH AHMBA ALMA_UNASSIGNED_HOLDINGS AOIJS APEBS ARAPS ATCPS BAIFH BAWUL BBNVY BBTPI BCNDV BENPR BGLVJ BHPHI BKEYQ BPHCQ BVXVI BWKFM CCPQU CITATION CS3 D1I D1J D1K DIK DU5 E3Z EAP EAS EBD EMOBN ESX EX3 F5P FPL FYUFA GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE IAO IEA IGS IHR IHW INH INR IOV IPY ISE ISR ITC K6- KB. KQ8 L6V LK5 LK8 M0K M1P M48 M7P M7R M7S M~E NAPCQ O5R O5S OK1 OVT P2P P62 PATMY PDBOC PHGZM PHGZT PIMPY PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PTHSS PV9 PYCSY RNS RPM RZL SV3 TR2 UKHRP WOQ WOW ~02 ~KM ALIPV CGR CUY CVF ECM EIF IPNFZ NPM RIG BBORY 3V. 7QG 7QL 7QO 7SN 7SS 7T5 7TG 7TM 7U9 7XB 8FD 8FK AZQEC C1K DWQXO ESTFP FR3 GNUQQ H94 K9. KL. M7N P64 PKEHL PQEST PQUKI PRINS RC3 7X8 5PM AAPBV ABPTK N95 |
| ID | FETCH-LOGICAL-c725t-6c6ba36c5c61eb4dabd1207919519c1a3f0b1a3c7895b6131a87594ac033e9a93 |
| IEDL.DBID | FPL |
| ISICitedReferencesCount | 152 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000378914900026&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1932-6203 |
| IngestDate | Sun Apr 02 01:15:44 EDT 2023 Fri Oct 03 12:40:23 EDT 2025 Tue Nov 04 01:57:38 EST 2025 Tue Oct 07 09:46:53 EDT 2025 Sun Nov 09 13:38:11 EST 2025 Tue Oct 07 07:51:51 EDT 2025 Sat Nov 29 13:14:12 EST 2025 Sat Nov 29 10:18:57 EST 2025 Wed Nov 26 10:11:25 EST 2025 Wed Nov 26 10:39:48 EST 2025 Thu May 22 21:20:37 EDT 2025 Mon Jul 21 06:03:11 EDT 2025 Tue Nov 18 22:33:49 EST 2025 Sat Nov 29 07:46:17 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 7 |
| Language | English |
| License | This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Creative Commons Attribution License |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c725t-6c6ba36c5c61eb4dabd1207919519c1a3f0b1a3c7895b6131a87594ac033e9a93 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: ENS KB SM BW. Performed the experiments: ENS KB. Analyzed the data: ENS KB. Wrote the paper: ENS KB SM BW. |
| OpenAccessLink | http://dx.doi.org/10.1371/journal.pone.0158248 |
| PMID | 27367425 |
| PQID | 1801026411 |
| PQPubID | 1436336 |
| ParticipantIDs | plos_journals_1801026411 doaj_primary_oai_doaj_org_article_3008bca3632a49fabd381d243fc75338 pubmedcentral_primary_oai_pubmedcentral_nih_gov_4930218 proquest_miscellaneous_1808729738 proquest_miscellaneous_1801434200 proquest_journals_1801026411 gale_infotracmisc_A456739860 gale_infotracacademiconefile_A456739860 gale_incontextgauss_ISR_A456739860 gale_incontextgauss_IOV_A456739860 gale_healthsolutions_A456739860 pubmed_primary_27367425 crossref_primary_10_1371_journal_pone_0158248 crossref_citationtrail_10_1371_journal_pone_0158248 |
| PublicationCentury | 2000 |
| PublicationDate | 2016-07-01 |
| PublicationDateYYYYMMDD | 2016-07-01 |
| PublicationDate_xml | – month: 07 year: 2016 text: 2016-07-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: San Francisco – name: San Francisco, CA USA |
| PublicationTitle | PloS one |
| PublicationTitleAlternate | PLoS One |
| PublicationYear | 2016 |
| Publisher | Public Library of Science Public Library of Science (PLoS) |
| Publisher_xml | – name: Public Library of Science – name: Public Library of Science (PLoS) |
| References | BS Halpern (ref1) 2008; 319 ref12 C Calenge (ref26) 2006; 197 ref36 J Lee (ref9) 2010; 67 K Skaar (ref8) 2011 ref11 ref33 WV Winkle (ref30) 1975; 39 ref17 ref39 ref38 E Walker (ref13) 2010; 221 M Lavielle (ref25) 2005; 85 ref18 D Peel (ref22) 2011; 68 J Carson-Jackson (ref34) 2012; 65 DJ McCauley (ref42) 2016; 351 MJ Witt (ref32) 2007; 2 L Torgo (ref19) 2010 DG Altman (ref20) 1994; 309 MA Cervera (ref35) 2011; 29 F Natale (ref4) 2015; 10 D Alemany (ref10) 2013; 70 R Trebilco (ref2) 2011; 144 H Gerritsen (ref6) 2011; 68 C Shui-Kai (ref5) 2014; 71 O Perpiñán (ref16) 2012; 50 AR Johnson (ref29) 1992; 73 Y Vermard (ref31) 2010; 221 P Fauchald (ref27) 2003; 84 BJ Worton (ref28) 1995; 59 ref7 WR Cairns (ref41) 2005; 58 C Charles (ref23) 2014; 71 M Lavielle (ref24) 1999; 83 S Bertrand (ref15) 2005; 62 G Pallotta (ref37) 2013; 15 N Bez (ref14) 2011; 68 ER Selig (ref3) 2014; 9 ref40 Z Ghahramani (ref21) 2002 18276889 - Science. 2008 Feb 15;319(5865):948-52 26098430 - PLoS One. 2015 Jun 22;10(6):e0130746 8038641 - BMJ. 1994 Jul 9;309(6947):102 26965610 - Science. 2016 Mar 11;351(6278):1148-50 17971874 - PLoS One. 2007 Oct 31;2(10):e1111 24416151 - PLoS One. 2014 Jan 08;9(1):e82898 27657928 - PLoS One. 2016;11(9):e0163760 |
| References_xml | – volume: 68 start-page: 245 issue: 1 year: 2011 ident: ref6 article-title: Integrating vessel monitoring systems (VMS) data with daily catch data from logbooks to explore the spatial distribution of catch and effort at high resolution publication-title: ICES Journal of Marine Science: Journal du Conseil doi: 10.1093/icesjms/fsq137 – ident: ref39 – ident: ref7 – volume: 85 start-page: 1501 issue: 8 year: 2005 ident: ref25 article-title: Using penalized contrasts for the change-point problem publication-title: Signal Processing doi: 10.1016/j.sigpro.2005.01.012 – volume: 319 start-page: 948 issue: 5865 year: 2008 ident: ref1 article-title: A global map of human impact on marine ecosystems publication-title: Science doi: 10.1126/science.1149345 – volume: 71 start-page: 1363 issue: 9 year: 2014 ident: ref5 article-title: Deriving high-resolution spatiotemporal fishing effort of large-scale longline fishery from vessel monitoring system (VMS) data and validated by observer data publication-title: Canadian Journal of Fisheries and Aquatic Sciences doi: 10.1139/cjfas-2013-0552 – year: 2011 ident: ref8 article-title: Accuracy of VMS data from Norwegian demersal stern trawlers for estimating trawled areas in the Barents Sea publication-title: ICES Journal of Marine Science: Journal du Conseil – volume: 73 start-page: 1968 issue: 6 year: 1992 ident: ref29 article-title: Diffusion in Fractcal Landscapes: Simulations and Experimental Studies of Tenebrionid Beetle Movements publication-title: Ecology doi: 10.2307/1941448 – volume: 351 start-page: 1148 issue: 6278 year: 2016 ident: ref42 article-title: Ending hide and go seek in the oceans publication-title: Science doi: 10.1126/science.aad5686 – volume: 67 start-page: 1260 issue: 6 year: 2010 ident: ref9 article-title: Developing reliable, repeatable, and accessible methods to provide high-resolution estimates of fishing-effort distributions from vessel monitoring system (VMS) data publication-title: ICES Journal of Marine Science: Journal du Conseil doi: 10.1093/icesjms/fsq010 – volume: 221 start-page: 2008 issue: 17 year: 2010 ident: ref13 article-title: A pioneer validation of a state-space model of vessel trajectories (VMS) with observers’ data publication-title: Ecological Modelling doi: 10.1016/j.ecolmodel.2010.05.007 – volume: 59 start-page: 794 issue: 4 year: 1995 ident: ref28 article-title: Using Monte Carlo Simulation to Evaluate Kernel-Based Home Range Estimators publication-title: The Journal of Wildlife Management doi: 10.2307/3801959 – ident: ref11 doi: 10.1109/SDF.2015.7347707 – ident: ref33 doi: 10.1109/OCEANSE.2009.5278254 – ident: ref36 doi: 10.1109/SPSC.2008.4686715 – volume: 62 start-page: 477 issue: 3 year: 2005 ident: ref15 article-title: Levy trajectories of Peruvian purse-seiners as an indicator of the spatial distribution of anchovy (Engraulis ringens) publication-title: ICES Journal of Marine Science: Journal du Conseil doi: 10.1016/j.icesjms.2004.12.002 – volume: 309 start-page: 102 issue: 6947 year: 1994 ident: ref20 article-title: Diagnostic tests 2: Predictive values publication-title: BMJ doi: 10.1136/bmj.309.6947.102 – volume: 58 start-page: 181 issue: 02 year: 2005 ident: ref41 article-title: AIS and long range identification & tracking publication-title: Journal of Navigation doi: 10.1017/S0373463305003267 – volume: 65 start-page: 303 issue: 02 year: 2012 ident: ref34 article-title: Satellite AIS–Developing Technology or Existing Capability? publication-title: Journal of Navigation doi: 10.1017/S037346331100066X – ident: ref17 – year: 2010 ident: ref19 article-title: Data Mining with R, learning with case studies – volume: 68 start-page: 1252 issue: 7 year: 2011 ident: ref22 article-title: A hidden Markov model approach for determining vessel activity from vessel monitoring system data publication-title: Canadian Journal of Fisheries and Aquatic Sciences doi: 10.1139/f2011-055 – ident: ref40 doi: 10.1109/BigData.2014.7004281 – ident: ref38 – volume: 10 start-page: e0130746 issue: 6 year: 2015 ident: ref4 article-title: Mapping Fishing Effort through AIS Data publication-title: PLoS ONE doi: 10.1371/journal.pone.0130746 – volume: 83 start-page: 79 issue: 1 year: 1999 ident: ref24 article-title: Detection of multiple changes in a sequence of dependent variables publication-title: Stochastic Processes and their Applications doi: 10.1016/S0304-4149(99)00023-X – volume: 9 start-page: e82898 issue: 1 year: 2014 ident: ref3 article-title: Global priorities for marine biodiversity conservation publication-title: PloS one doi: 10.1371/journal.pone.0082898 – volume: 70 start-page: 123 issue: 1 year: 2013 ident: ref10 article-title: Effects of a large-scale and offshore marine protected area on the demersal fish assemblage in the Southwest Atlantic publication-title: ICES Journal of Marine Science: Journal du Conseil doi: 10.1093/icesjms/fss166 – volume: 197 start-page: 1035 year: 2006 ident: ref26 article-title: The package adehabitat for the R software: tool for the analysis of space and habitat use by animals publication-title: Ecological Modelling doi: 10.1016/j.ecolmodel.2006.03.017 – volume: 50 start-page: 1 issue: 9 year: 2012 ident: ref16 article-title: solaR: Solar Radiation and Photovoltaic Systems with R publication-title: Journal of Statistical Software doi: 10.18637/jss.v050.i09 – start-page: 9 year: 2002 ident: ref21 article-title: Hidden Markov Models – volume: 144 start-page: 1758 issue: 5 year: 2011 ident: ref2 article-title: Mapping species richness and human impact drivers to inform global pelagic conservation prioritisation publication-title: Biological Conservation doi: 10.1016/j.biocon.2011.02.024 – volume: 39 start-page: 118 issue: 1 year: 1975 ident: ref30 article-title: Comparison of Several Probabilistic Home-Range Models publication-title: The Journal of Wildlife Management doi: 10.2307/3800474 – volume: 84 start-page: 282 year: 2003 ident: ref27 article-title: Using First-Passage Time in the Analysis of Area-Restricted Search and Habitat Selection publication-title: Ecology doi: 10.1890/0012-9658(2003)084[0282:UFPTIT]2.0.CO;2 – ident: ref18 – volume: 29 start-page: 117 issue: 2 year: 2011 ident: ref35 article-title: Satellite-based vessel Automatic Identification System: A feasibility and performance analysis publication-title: International Journal of Satellite Communications and Networking doi: 10.1002/sat.957 – volume: 68 start-page: 1998 issue: 11 year: 2011 ident: ref14 article-title: Fishing activity of tuna purse seiners estimated from vessel monitoring system (VMS) data publication-title: Canadian Journal of Fisheries and Aquatic Sciences doi: 10.1139/f2011-114 – volume: 71 start-page: 1817 issue: 12 year: 2014 ident: ref23 article-title: Using hidden Markov models to infer vessel activities in the snow crab (Chionoecetes opilio) fixed gear fishery and their application to catch standardization publication-title: Canadian Journal of Fisheries and Aquatic Sciences doi: 10.1139/cjfas-2013-0572 – volume: 221 start-page: 1757 issue: 15 year: 2010 ident: ref31 article-title: Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models publication-title: Ecological Modelling doi: 10.1016/j.ecolmodel.2010.04.005 – volume: 2 start-page: e1111 issue: 10 year: 2007 ident: ref32 article-title: A step towards seascape scale conservation: using vessel monitoring systems (VMS) to map fishing activity publication-title: PloS one doi: 10.1371/journal.pone.0001111 – volume: 15 start-page: 2218 issue: 6 year: 2013 ident: ref37 article-title: Vessel pattern knowledge discovery from AIS data: A framework for anomaly detection and route prediction publication-title: Entropy doi: 10.3390/e15062218 – ident: ref12 – reference: 8038641 - BMJ. 1994 Jul 9;309(6947):102 – reference: 24416151 - PLoS One. 2014 Jan 08;9(1):e82898 – reference: 26965610 - Science. 2016 Mar 11;351(6278):1148-50 – reference: 26098430 - PLoS One. 2015 Jun 22;10(6):e0130746 – reference: 17971874 - PLoS One. 2007 Oct 31;2(10):e1111 – reference: 18276889 - Science. 2008 Feb 15;319(5865):948-52 – reference: 27657928 - PLoS One. 2016;11(9):e0163760 |
| SSID | ssj0053866 |
| Score | 2.6064546 |
| Snippet | A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While... |
| SourceID | plos doaj pubmedcentral proquest gale pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | e0158248 |
| SubjectTerms | Algorithms Analysis Animals Aquatic sciences Artificial intelligence Biology and Life Sciences Chionoecetes opilio Coastal fisheries Coastal waters Computer and Information Sciences Computer science Conservation Data analysis Data mining Data Mining - methods Data processing Earth Sciences Ecology Ecology and Environmental Sciences Environmental protection Filtration Fisheries Fisheries - statistics & numerical data Fisheries management Fishery management Fishing Fishing equipment Fishing gear Fishing tackle Fishing vessels Ground stations Human influences Identification systems Information systems International conferences Learning algorithms Machine Learning Markov chains Methods Monte Carlo simulation Multilayers Oceans Pattern Recognition, Automated - methods Physical sciences Protection and preservation Research and Analysis Methods Satellite communications Seiners Signal processing Spacecraft Spatial distribution Temporal distribution Trawlers |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3db9MwELdQtQdeEONrHQMMQgIesiWxa8ePhVExiY2JAtoLipyLPSZNabWk-_s5fzRq0MR44KUP8SVqf3fnO6d3vyPktQWeg0BPE8IUCTfAEzUp6sQIDVAUqoIwteSzPDkpzs7U6caoL1cTFuiBA3AHDINUBZoJlmuurK5qjDF1zpkFzLSZb_NNpVofpsIejF4sRGyUYzI7iHrZXy4as48BsMjdvJ-NQOT5-vtdebS8XLQ3pZx_Vk5uhKLZfXIv5pB0Gr77NrljmgdkO3ppS99GKul3D8nP_p0BnYWXTfTUE2o29NB0vgqroa7DhM61p-bsDJ0ezakvJKCHutP02E-QoLqp6bEvvDQ0crKePyLfZx-_ffiUxIEKCch80iUCRIVIwgREZipeI5iZAy_DNEtBpplNK_wEWahJhXE-03iaUVxDyphRWrHHZNQghDuEpja3VtoaRG25kaA55g6V1ayaZJqbekzYGt0SItu4G3pxWfq_0CSeOgJYpdNJGXUyJkl_1zKwbdwi_94prpd1XNn-AlpQGS2ovM2CxuSFU3sZGk97jy-nmFtKpgqRjskrL-H4MhpXkHOuV21bHn358Q9C868DoTdRyC4QDtCxCQJ_k-PhGkjuDSTR62GwvOOMdI1KW2aFYwcUPMvwzrXh3rz8sl92D3VFdo1ZrIIMZxz3zb_KFNLNO0PYngRf6NHHTFhIjAFjIgdeMlDPcKW5-OUpzbliLtnc_R_6fEruYlYrQk31Hhl1VyvzjGzBdXfRXj33-8RvI1dtSg priority: 102 providerName: Directory of Open Access Journals – databaseName: Nursing & Allied Health Database dbid: 7RV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3Nb9MwFLeggMSFsfKxwgCDkIBDtjp27fiECtvEJDamFaZdUOQ4dpk0JaVJkfjveXacsKBpIHHJIX6JYr8P_-w8_x5CL61msebgaZybJGJGs0hOkjwyXGmdJDLTTdWSj-LwMDk9lUdhw60KaZVtTPSBOi-12yPfJoljP-OMkLeL75GrGuX-roYSGtfRDeKwMdizOD5pIzH4MufhuBwVZDtoZ2tRFmYLpsEkdlV_LkxHnrW_i82DxXlZXQY8_8yfvDAh7a39b1fuojsBiuJpYzvr6JophmitLfOAg9cP0a1dz2z9c4jWw70Kvw501W_uoa_dvgTeaza08JEn7Szwjql9pleB3SkWPFOe_rM2eLo_wz5ZAe-oWuEDX6UCqyLHBz650-DA-zq_j77s7X5-_yEKRRsiLeJJHXHNM0W5nmhOTMZyleUkHgtJAMpJTRS14wyuWiRykgGWIApWTJIpPabUSCXpAzQoQEEbCI9tbK2wuea5ZUZoxQCfZFbRbEIUM_kI0VZ3qQ6M5q6wxnnqf9MJWNk0I5k6jadB4yMUdU8tGkaPv8i_c2bRyTo-bn-jXM7T4N4pBSiVaeg3jRWTFjoNSCiPGbUa1oMUXvLMGVXaHG7toko6BfwqqEz4eIReeAnHyVG4pJ-5WlVVuv_p5B-EZsc9oVdByJYwHFqFgxbQJ8f11ZPc7ElCZNG95g3nAu2oVOlvw4UnW9O-vPl51-xe6hL5ClOuGhlGGcTmK2US4WqqwbA9bDytG31A21zAPDNCoueDPfX0W4qzb542nUnqAO2jqz_9MboNmJg3GdmbaFAvV-YJuql_1GfV8qmPL78AEUuE3Q priority: 102 providerName: ProQuest |
| Title | Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/27367425 https://www.proquest.com/docview/1801026411 https://www.proquest.com/docview/1801434200 https://www.proquest.com/docview/1808729738 https://pubmed.ncbi.nlm.nih.gov/PMC4930218 https://doaj.org/article/3008bca3632a49fabd381d243fc75338 http://dx.doi.org/10.1371/journal.pone.0158248 |
| Volume | 11 |
| WOSCitedRecordID | wos000378914900026&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: DOA dateStart: 20060101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M~E dateStart: 20060101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: P5Z dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Agricultural Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M0K dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/agriculturejournals providerName: ProQuest – providerCode: PRVPQU databaseName: Biological Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M7P dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/biologicalscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Engineering Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: M7S dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com providerName: ProQuest – providerCode: PRVPQU databaseName: Environmental Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: PATMY dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/environmentalscience providerName: ProQuest – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 7X7 dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: Materials Science Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: KB. dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/materialsscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Nursing & Allied Health Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 7RV dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/nahs providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: BENPR dateStart: 20061201 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Publicly Available Content Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: PIMPY dateStart: 20061201 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVPQU databaseName: Public Health Database customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: 8C1 dateStart: 20061201 isFulltext: true titleUrlDefault: https://search.proquest.com/publichealth providerName: ProQuest – providerCode: PRVATS databaseName: Public Library of Science (PLoS) Journals Open Access customDbUrl: eissn: 1932-6203 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0053866 issn: 1932-6203 databaseCode: FPL dateStart: 20060101 isFulltext: true titleUrlDefault: http://www.plos.org/publications/ providerName: Public Library of Science |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3db9MwELdYBxIvjJWPFUYxCAl4SEli13Ye260V1dYSrTAVJBQ5jjMmTWm1tkj895wdN5Bp4-PlHuJzFJ999s_O-XcIvcoVDRUDT2NMC49qRb2oKzJPM6mUEFGqyqwlx3wyEbNZFP_aKF75g0948M7ZtLOYF7oDi5cIqdhC2yFhzKRqGMbHm5kXfJcxdz3uppq15cey9FdzcWNxMV9eBzSvxkv-tgANd_730--jew5q4l45NnbRLV000c4mjQN2Xt1EdwaWufpHE-26Z0v8xtFRv32AvlbnDnhYHljh2JJyFvhQr2wkV4HNLRU8lZbec6VxbzTFNhgBH8qVxGObhQLLIsNjG7ypseN1PXuIPg0HHw_eey4pg6d42F15TLFUEqa6igU6pZlMsyD0eRQAVItUIEnupyAVF1E3BawQSNgRRVQqnxAdyYg8Qo0C7LGHsJ-Hec7zTLEsp5orSQF_pLkkaTeQVGctRDZ9lSjHWG4SZ1wk9jcch51LacnEGDhxBm4hr6q1KBk7_qLfN8Og0jV82_YB9GTi3DchAJVSBe0moaRRDo0GpJOFlOQK9nsEXvLcDKKkvLxazRpJD_ApJ5Fgfgu9tBqGc6MwQT1ncr1cJqMPp_-gND2pKb12SvkczKGku0gBbTJcXjXN_ZomzByqVrxnhvzGKsskEIZhkNEggJobN7i--EVVbF5qAvUKPV-XOpRQmHv_qCO4yZkGZntcelZlfUDTjMM60kK85nO17qmXFOffLC06jYgBrE9ubtVTdBfwLiujrfdRY3W51s_QbfV9db68bKMtfnJq5IxbKUCKg6CNtvuDSXzStsc1bTvjgDzqd0CO_SMjeWzlFGTc_QI14tE4_vwTfxZ_wA |
| linkProvider | Public Library of Science |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3Nb9MwFLemAYILY-VjhcEMAgGHbE3s2skBobKuWrW2THSgXVBwHKdMmpLSpKD9U_yNPDtOWNA0uOzApYf4Japf3sfPzvPvIfQ8kdSTDDyNMeU7VEnqBF0_dhQTUvp-EMmya8mITyb-8XFwuIJ-VmdhdFllFRNNoI4zqffId1xfs58x6rpv598c3TVKf12tWmiUZnGgzn7Aki1_M-zD-33heYO9o919x3YVcCT3uoXDJIsEYbIrmasiGosodr0OD1zAGoF0BUk6EfxK7gfdCJKdKwDSB1TIDiEqEJp8CUL-NUo8or3I361LSiB2MGaP5xHu7lhr2J5nqdqGtOt7usvQufRnugTUuWB1fprlFwHdP-s1zyXAwdr_pro76LaF2rhX-sY6WlFpC61VbSywjWotdGPPMHeftdC6vZbjV5aO-_Vd9Lned8GDcsMOHxpS0hT3VWEq2VKsT-ngqTD0poXCveEUm2IM3BeFwGPThQOLNMZjU7yqsOW1nd1DH69EB_fRagoGsYFwJ_GShCexZHFCFZeCAv6KEkGiriuoituIVLYSSsvYrhuHnIbmMySHlVupyVBbWGgtrI2c-q55yVjyF_l32gxrWc03bi5ki1low1dIACpGEuZNPEGDBCYNSC_2KEkkrHcJPGRLG3FYHt6to2bYA3zOSeCzThs9MxKacyTVRU0zsczzcPj-0z8ITT80hF5aoSQDdUhhD5LAnDSXWUNysyEJkVM2hje0y1VaycPfjgJ3Vq508fDTelg_VBcqpipbljKUUMg9l8r4XPeMA7U9KD271j6sJhiHPNpGvOHzjdfTHElPvhpaeBoQDdgfXv7Xt9DN_aPxKBwNJweP0C3A_6ysPt9Eq8ViqR6j6_J7cZIvnpjYhtGXq44IvwCI4uBV |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3db9MwELem8iFeGCsfKwxmEAh4yNrErp08IFToKqptpaID7QUFx3HKpCkpTQrav8Zfx9lxwoKmwcseeOlDfInqy93vzs75dwg9TST1JANPY0z5DlWSOkHfjx3FhJS-H0Sy7FqyzycT_-gomK6hn9VZGF1WWWGiAeo4k3qPvOv6mv2MUdftJrYsYjocvV58c3QHKf2ltWqnUZrInjr9Acu3_NV4CO_6meeNdg_fvnNshwFHcq9fOEyySBAm-5K5KqKxiGLX6_HAhbwjkK4gSS-CX8n9oB9B4HMFpPcBFbJHiAqEJmIC-L_CKczWlA1OqygAOMKYPapHuNu1lrGzyFK1AyHY93THoTOh0HQMqONCa3GS5eclvX_Wbp4JhqP1_1mNt9BNm4LjQekzG2hNpW20XrW3wBbt2ujarmH0Pm2jDXstxy8sTffL2-hzvR-DR-VGHp4astIUD1VhKtxSrE_v4JkwtKeFwoPxDJsiDTwUhcAHpjsHFmmMD0xRq8KW73Z-B328FB3cRa0UjGMT4V7iJQlPYsnihCouBYW8LEoEifquoCruIFLZTSgtk7tuKHISms-THFZ0pSZDbW2htbYOcuq7FiWTyV_k32iTrGU1D7m5kC3noYW1kEAKGUmYN_EEDRKYNGSAsUdJImEdTOAh29qgw_JQb42m4QDydk4Cn_U66ImR0FwkqTbHuVjleTh-_-kfhGYfGkLPrVCSgTqksAdMYE6a46whudWQBESVjeFN7X6VVvLwt9PAnZVbnT_8uB7WD9UFjKnKVqUMJRRi0oUyPte95EBt90ovr7UPqwzGIb52EG_4f-P1NEfS46-GLp4GRCfy9y_-69voOgBBuD-e7D1AN2BZwMqi9C3UKpYr9RBdld-L43z5yMAcRl8uGxB-AfG-6WE |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Improving+Fishing+Pattern+Detection+from+Satellite+AIS+Using+Data+Mining+and+Machine+Learning&rft.jtitle=PloS+one&rft.au=Souza%2C+Erico+Nde&rft.au=Boerder%2C+Kristina&rft.au=Matwin%2C+Stan&rft.au=Worm%2C+Boris&rft.date=2016-07-01&rft.eissn=1932-6203&rft.volume=11&rft.issue=7&rft_id=info:doi/10.1371%2Fjournal.pone.0158248&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1932-6203&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1932-6203&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1932-6203&client=summon |