Published June 1, 2025
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Journal article
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Automated Mangrove Detection Method using Combined Machine Learning and Mangrove Index over Indonesia
Authors/Creators
- 1. Research Organization for
Description
The carbon storage potential of mangrove forests is higher than highland tropical forests. It makes mapping mangroves essential to estimate a total carbon storage potential. Integration of satellite data which covers a wide area and machine learning can obtain mangrove detection to be faster and more accurate. The study proposes an automated mangrove detection method using a combined mangrove index and machine learning over Indonesia. Normalized Difference Moisture Index and Mangrove Vegetation Index from Landsat 8/9 images were used to obtain training datasets for the Random Forest process. The results show that the overall accuracy is 0.93, and the kappa accuracy is 0.91. It proves that the proposed method can be used for mapping mangroves and non-mangroves accurately.
Notes
Published in Evergreen, Volume 12, Issue 02. Citation formats available via DOI link.
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p885-894.pdf
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Related works
- Is identical to
- Journal article: 10.5109/7363482 (DOI)
- Is supplemented by
- Other: https://citation.crossref.org/?doi=10.5109/7363482 (URL)