Digital detection of Acacia Mangium trees via remote sensing for controlling the invasive population of biodiversity threats: Case study in Brunei

Moad Idrissi, Ahmad Najiy Wahab, Dalia El-Banna, Daphne Lai, Ferry Slik, Taufiq Asyhari

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Abstract

The growth of invasive Acacia Mangium has presented a new biodiversity threat to Brunei, which is situated on the biologically diverse island of Borneo. Hazards to the native flora due to Acacia's fast invasion and threats to forest fires have resulted in increased risks of burnable oil. In line with Brunei's National Climate Change Policy, which is reflected in Brunei Vision 2035, it is crucial to conserve Brunei's extensive forest cover by proactive management of the Acacia population in the country's tropical rainforests. Therefore, In line with Brunei's National Climate Change Policy, which is reflected in the Brunei vision, active management of the Acacia population in Brunei's rainforests is considered crucial as it can determine and scope out the country's extensive forest cover. In order to identify the species of Acacia tree and the coverage, this study uses UAV-based, high-resolution RGB photos that have been analysed by machine learning software. The images captured are tested and analysed using a convolutional neural network (CNN) model which is trained to detect the Acacia tree species highlighting regions that indicated a maximum accuracy of 84% based on the manually annotated datasets.

Original languageEnglish
Title of host publicationProceedings of the 2023 12th International Conference on Informatics, Environment, Energy and Applications, IEEA 2023
EditorsChavalit Ratanathamsakul, Frank Gunzer, Dongsheng Cai, Xiaowei Zhai
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages27-32
Number of pages6
ISBN (Electronic)9798400700125
DOIs
Publication statusPublished - 2023
Externally publishedYes
EventInternational Conference on Informatics, Environment, Energy and Applications 2023 - Singapore, Singapore
Duration: 17 Feb 202319 Feb 2023
Conference number: 12th
https://dl.acm.org/doi/proceedings/10.1145/3594692 (Proceedings)
http://ieea.org/ (Website)

Conference

ConferenceInternational Conference on Informatics, Environment, Energy and Applications 2023
Abbreviated titleIEEA 2023
Country/TerritorySingapore
CitySingapore
Period17/02/2319/02/23
Internet address

Keywords

  • Acacia Mangium
  • Artificial Intelligence
  • Convoilutional Neural Network (CNN)
  • UAV

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