FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4291018766> ?p ?o ?g. }

• W4291018766 abstract "Detecting changes in population trends depends on the accuracy of estimated mean population growth rates and thus the quality of input data. However, monitoring wildlife populations poses economic and logistic challenges especially in complex and remote habitats. Declines in wildlife populations can remain undetected for years unless effective monitoring techniques are developed, guiding appropriate management actions. We developed an automated survey workflow using unmanned aerial vehicles (drones) to quantify the number and size of individual animals, using the well-studied Scandinavian harbour seal ( Phoca vitulina ) as a model species. We compared ground-based counts using telescopes with manual flights, using a zoom photo/video, and pre-programmed flights producing orthomosaic photo maps. We used machine learning to identify and count both pups and older seals and we present a new method for measuring body size automatically. We evaluate the population’s reproductive success using drone data, historical counts and predictions from a Leslie matrix population model. The most accurate and time-efficient results were achieved by performing pre-programmed flights where individual seals are identified by machine learning and their body sizes are measured automatically. The accuracy of the machine learning detector was 95–97% and the classification error was 4.6 ± 2.9 for pups and 3.1 ± 2.1 for older seals during good light conditions. There was a clear distinction between the body sizes of pups and older seals during breeding time. We estimated 320 pups in the breeding season 2021 with the drone, which is well beyond the expected number, based on historical data on pup production. The new high quality data from the drone survey confirms earlier indications of a deteriorating reproductive rate in this important harbour seal colony. We show that aerial drones and machine learning are powerful tools for monitoring wildlife in inaccessible areas which can be used to assess annual recruitment and seasonal variations in body condition." @default.
• W4291018766 created "2022-08-13" @default.
• W4291018766 creator A5004495187 @default.
• W4291018766 creator A5009581966 @default.
• W4291018766 creator A5033082627 @default.
• W4291018766 creator A5038936000 @default.
• W4291018766 creator A5040485140 @default.
• W4291018766 creator A5071976633 @default.
• W4291018766 date "2022-08-11" @default.
• W4291018766 modified "2023-10-11" @default.
• W4291018766 title "An automated work-flow for pinniped surveys: A new tool for monitoring population dynamics" @default.
• W4291018766 cites W1901129140 @default.
• W4291018766 cites W1951724000 @default.
• W4291018766 cites W1970604559 @default.
• W4291018766 cites W2026610207 @default.
• W4291018766 cites W2051481085 @default.
• W4291018766 cites W2057784151 @default.
• W4291018766 cites W2067556932 @default.
• W4291018766 cites W2068135227 @default.
• W4291018766 cites W2082332703 @default.
• W4291018766 cites W2091695913 @default.
• W4291018766 cites W2101448560 @default.
• W4291018766 cites W2103182063 @default.
• W4291018766 cites W2112433083 @default.
• W4291018766 cites W2128599926 @default.
• W4291018766 cites W2140047826 @default.
• W4291018766 cites W2140813774 @default.
• W4291018766 cites W2143897835 @default.
• W4291018766 cites W2144717685 @default.
• W4291018766 cites W2145883134 @default.
• W4291018766 cites W2170219589 @default.
• W4291018766 cites W2323722282 @default.
• W4291018766 cites W2331725058 @default.
• W4291018766 cites W2464021962 @default.
• W4291018766 cites W2527949113 @default.
• W4291018766 cites W2598225981 @default.
• W4291018766 cites W2621822939 @default.
• W4291018766 cites W2737340643 @default.
• W4291018766 cites W2741495483 @default.
• W4291018766 cites W2751948458 @default.
• W4291018766 cites W2752508182 @default.
• W4291018766 cites W2767083027 @default.
• W4291018766 cites W2794256331 @default.
• W4291018766 cites W2800586067 @default.
• W4291018766 cites W2802498826 @default.
• W4291018766 cites W2804233742 @default.
• W4291018766 cites W2810030371 @default.
• W4291018766 cites W2891073780 @default.
• W4291018766 cites W2894730400 @default.
• W4291018766 cites W2922474262 @default.
• W4291018766 cites W2923133959 @default.
• W4291018766 cites W2930426867 @default.
• W4291018766 cites W2936137334 @default.
• W4291018766 cites W2945020140 @default.
• W4291018766 cites W2948178929 @default.
• W4291018766 cites W2978243898 @default.
• W4291018766 cites W2993858625 @default.
• W4291018766 cites W3013690456 @default.
• W4291018766 cites W3023987551 @default.
• W4291018766 cites W3042604815 @default.
• W4291018766 cites W3099507214 @default.
• W4291018766 cites W3124725594 @default.
• W4291018766 cites W3131388338 @default.
• W4291018766 cites W3133528540 @default.
• W4291018766 cites W3136112459 @default.
• W4291018766 cites W3153421944 @default.
• W4291018766 cites W3166996469 @default.
• W4291018766 cites W3189877312 @default.
• W4291018766 cites W3200944103 @default.
• W4291018766 cites W4210883322 @default.
• W4291018766 cites W4212782080 @default.
• W4291018766 cites W4234971943 @default.
• W4291018766 cites W4234980865 @default.
• W4291018766 cites W4248856567 @default.
• W4291018766 cites W639708223 @default.
• W4291018766 doi "https://doi.org/10.3389/fevo.2022.905309" @default.
• W4291018766 hasPublicationYear "2022" @default.
• W4291018766 type Work @default.
• W4291018766 citedByCount "4" @default.
• W4291018766 countsByYear W42910187662023 @default.
• W4291018766 crossrefType "journal-article" @default.
• W4291018766 hasAuthorship W4291018766A5004495187 @default.
• W4291018766 hasAuthorship W4291018766A5009581966 @default.
• W4291018766 hasAuthorship W4291018766A5033082627 @default.
• W4291018766 hasAuthorship W4291018766A5038936000 @default.
• W4291018766 hasAuthorship W4291018766A5040485140 @default.
• W4291018766 hasAuthorship W4291018766A5071976633 @default.
• W4291018766 hasBestOaLocation W42910187661 @default.
• W4291018766 hasConcept C102874275 @default.
• W4291018766 hasConcept C119857082 @default.
• W4291018766 hasConcept C144024400 @default.
• W4291018766 hasConcept C149923435 @default.
• W4291018766 hasConcept C176262533 @default.
• W4291018766 hasConcept C18903297 @default.
• W4291018766 hasConcept C205649164 @default.
• W4291018766 hasConcept C2780457584 @default.
• W4291018766 hasConcept C2908647359 @default.
• W4291018766 hasConcept C2909536952 @default.
• W4291018766 hasConcept C29376679 @default.
• W4291018766 hasConcept C36528806 @default.

• next