An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery
Acquiring tree-stump information is important to support post-harvest site assessment. Unmanned Aerial Vehicles (UAVs) have been widely used as a tool for analyzing selective logging impacts in forest area sites. One of the potential use of UAV imagery data for analyzing the impact of selective logg...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Penerbit Universiti Kebangsaan Malaysia
2021
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| Online Access: | http://journalarticle.ukm.my/18215/ http://journalarticle.ukm.my/18215/1/50000-172598-1-PB.pdf |
| _version_ | 1848814513261903872 |
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| author | Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud, |
| author_facet | Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud, |
| author_sort | Aisyah Marliza Muhmad Kamarulzaman, |
| building | UKM Institutional Repository |
| collection | Online Access |
| description | Acquiring tree-stump information is important to support post-harvest site assessment. Unmanned Aerial Vehicles (UAVs) have been widely used as a tool for analyzing selective logging impacts in forest area sites. One of the potential use of UAV imagery data for analyzing the impact of selective logging is by obtaining tree stump information. Feature extraction and segmentation images to extract stumps from a UAV scene of a forested area in Ulu Jelai, Pahang provides a quick, automated method for identifying stumps. This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. This study assessed the capability of an object-based approach on image detection to segment and merge the stumps after selective logging practice on UAV imagery with a scale of 0.06-meter resolution. The results revealed that the tree-stumps were detected with an accuracy of 70% and stumps classification were detected with 80% accuracy validated with the ground points. The accuracy is acceptable for data acquiring after 6 months of logging activities. The findings of this study are promising and can lead to increase support for a more cost-effective and systematic selective logging in the future. An effective management system can help related authorities and agencies to develop and maintain the selective logging technique towards sustainable forest management. |
| first_indexed | 2025-11-15T00:35:17Z |
| format | Article |
| id | oai:generic.eprints.org:18215 |
| institution | Universiti Kebangasaan Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T00:35:17Z |
| publishDate | 2021 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:generic.eprints.org:182152022-03-14T01:00:16Z http://journalarticle.ukm.my/18215/ An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud, Acquiring tree-stump information is important to support post-harvest site assessment. Unmanned Aerial Vehicles (UAVs) have been widely used as a tool for analyzing selective logging impacts in forest area sites. One of the potential use of UAV imagery data for analyzing the impact of selective logging is by obtaining tree stump information. Feature extraction and segmentation images to extract stumps from a UAV scene of a forested area in Ulu Jelai, Pahang provides a quick, automated method for identifying stumps. This research implemented a technique for detecting, segmenting, classifying, and measuring tree stumps by using the Multiresolution Segmentation Algorithm method. This study assessed the capability of an object-based approach on image detection to segment and merge the stumps after selective logging practice on UAV imagery with a scale of 0.06-meter resolution. The results revealed that the tree-stumps were detected with an accuracy of 70% and stumps classification were detected with 80% accuracy validated with the ground points. The accuracy is acceptable for data acquiring after 6 months of logging activities. The findings of this study are promising and can lead to increase support for a more cost-effective and systematic selective logging in the future. An effective management system can help related authorities and agencies to develop and maintain the selective logging technique towards sustainable forest management. Penerbit Universiti Kebangsaan Malaysia 2021 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/18215/1/50000-172598-1-PB.pdf Aisyah Marliza Muhmad Kamarulzaman, and Wan Shafrina Wan Mohd Jaafar, and Siti Nor Maizah Saad, and Hamdan Omar, and Mohd. Rizaludin Mahmud, (2021) An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery. Geografia : Malaysian Journal of Society and Space, 17 (4). pp. 353-365. ISSN 2180-2491 https://ejournal.ukm.my/gmjss/issue/view/1443 |
| spellingShingle | Aisyah Marliza Muhmad Kamarulzaman, Wan Shafrina Wan Mohd Jaafar, Siti Nor Maizah Saad, Hamdan Omar, Mohd. Rizaludin Mahmud, An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery |
| title | An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery |
| title_full | An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery |
| title_fullStr | An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery |
| title_full_unstemmed | An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery |
| title_short | An object-based approach to detect tree stumps in a selective logging area using Unmanned Aerial Vehicle imagery |
| title_sort | object-based approach to detect tree stumps in a selective logging area using unmanned aerial vehicle imagery |
| url | http://journalarticle.ukm.my/18215/ http://journalarticle.ukm.my/18215/ http://journalarticle.ukm.my/18215/1/50000-172598-1-PB.pdf |