Object detection in order to determine locations for wildlife crossings
The intensive construction of road infrastructure due to urbanization and industrialization around the world carries with it negative environmental impacts, primarily due to increased emissions of gases, but also due to the separation of natural habitats and ecosystems. In order to overcome this pro...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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University of Belgrade - Faculty of Geography, Belgrade
2022-01-01
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| Series: | Zbornik Radova: Geografski Fakultet Univerziteta u Beogradu |
| Subjects: | |
| Online Access: | https://scindeks-clanci.ceon.rs/data/pdf/1450-7552/2022/1450-75522270023V.pdf |
| _version_ | 1811314718768365568 |
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| author | Vagić Nemanja Peulić Aleksandar Stojković Sanja |
| author_facet | Vagić Nemanja Peulić Aleksandar Stojković Sanja |
| author_sort | Vagić Nemanja |
| collection | DOAJ |
| description | The intensive construction of road infrastructure due to urbanization and industrialization around the world carries with it negative environmental impacts, primarily due to increased emissions of gases, but also due to the separation of natural habitats and ecosystems. In order to overcome this problem, without affecting the mobility of the population, it is necessary to allow wild animals to cross over or below the roads, i.e. to create wildlife crossings, which requires knowledge of the locations where the corridors of animal movements intersect with existing or planned roads. This paper analysis the establishment of a camera system and the application of a deep learning methodology for the automatic identification of animals by species and number, in order to determine locations for the construction of crossings for large wildlife. Also, the paper presents the possibility of using geographic information systems to analyze information obtained by monitoring built wildlife crossings. |
| first_indexed | 2024-04-13T11:17:30Z |
| format | Article |
| id | doaj.art-4234603c514446bfa80575707ffec9e4 |
| institution | Directory Open Access Journal |
| issn | 1450-7552 2334-9441 |
| language | English |
| last_indexed | 2024-04-13T11:17:30Z |
| publishDate | 2022-01-01 |
| publisher | University of Belgrade - Faculty of Geography, Belgrade |
| record_format | Article |
| series | Zbornik Radova: Geografski Fakultet Univerziteta u Beogradu |
| spelling | doaj.art-4234603c514446bfa80575707ffec9e42022-12-22T02:48:55ZengUniversity of Belgrade - Faculty of Geography, BelgradeZbornik Radova: Geografski Fakultet Univerziteta u Beogradu1450-75522334-94412022-01-01202270233610.5937/zrgfub2270023V1450-75522270023VObject detection in order to determine locations for wildlife crossingsVagić Nemanja0https://orcid.org/0000-0002-8639-0585Peulić Aleksandar1https://orcid.org/0000-0003-0416-4056Stojković Sanja2https://orcid.org/0000-0003-2292-5082University of Belgrade, Faculty of Geography, Belgrade, SerbiaUniversity of Belgrade, Faculty of Geography, Belgrade, SerbiaUniversity of Belgrade, Faculty of Geography, Belgrade, SerbiaThe intensive construction of road infrastructure due to urbanization and industrialization around the world carries with it negative environmental impacts, primarily due to increased emissions of gases, but also due to the separation of natural habitats and ecosystems. In order to overcome this problem, without affecting the mobility of the population, it is necessary to allow wild animals to cross over or below the roads, i.e. to create wildlife crossings, which requires knowledge of the locations where the corridors of animal movements intersect with existing or planned roads. This paper analysis the establishment of a camera system and the application of a deep learning methodology for the automatic identification of animals by species and number, in order to determine locations for the construction of crossings for large wildlife. Also, the paper presents the possibility of using geographic information systems to analyze information obtained by monitoring built wildlife crossings.https://scindeks-clanci.ceon.rs/data/pdf/1450-7552/2022/1450-75522270023V.pdfdeep learninggisobject detectionwildlife crossings |
| spellingShingle | Vagić Nemanja Peulić Aleksandar Stojković Sanja Object detection in order to determine locations for wildlife crossings Zbornik Radova: Geografski Fakultet Univerziteta u Beogradu deep learning gis object detection wildlife crossings |
| title | Object detection in order to determine locations for wildlife crossings |
| title_full | Object detection in order to determine locations for wildlife crossings |
| title_fullStr | Object detection in order to determine locations for wildlife crossings |
| title_full_unstemmed | Object detection in order to determine locations for wildlife crossings |
| title_short | Object detection in order to determine locations for wildlife crossings |
| title_sort | object detection in order to determine locations for wildlife crossings |
| topic | deep learning gis object detection wildlife crossings |
| url | https://scindeks-clanci.ceon.rs/data/pdf/1450-7552/2022/1450-75522270023V.pdf |
| work_keys_str_mv | AT vagicnemanja objectdetectioninordertodeterminelocationsforwildlifecrossings AT peulicaleksandar objectdetectioninordertodeterminelocationsforwildlifecrossings AT stojkovicsanja objectdetectioninordertodeterminelocationsforwildlifecrossings |