Mapping of Mangrove Conditions Using Sentinel-2 Imagery

Authors

  • Dwi Rosalina Politeknik Kelautan dan Perikanan Bone, Bone, Indonesia
  • Anisa Aulia Sabilah Politeknik Kelautan dan Perikanan Bone, Bone, Indonesia
  • Katarina Hesty Rombe Politeknik Kelautan dan Perikanan Bone, Bone, Indonesia
  • Warni Politeknik Kelautan dan Perikanan Bone, Bone, Indonesia

DOI:

https://doi.org/10.23887/jstundiksha.v13i1.65281

Keywords:

Kerapatan, Mangrove, NDVI, Pulau Pannikiang

Abstract

Mangrove forests face significant pressure due to human activities such as illegal logging, land conversion, and pollution. The impact of human activities on this ecosystem has raised concerns about the degradation and loss of mangrove forests. This study aimed to analyze the condition of the mangrove ecosystem on Pannikiang Island through density and area analysis. Data was collected using remote sensing methods, such as Sentinel-2 satellite imagery, which has a spatial resolution of 10 meters. The instruments used include PC hardware, ENVI, and ArcGIS software for image processing. This type of research is quantitative descriptive research that utilizes remote sensing technology. The research subjects were all mangrove forests along Pannikiang Island with a total area of 1,042,261.12 m². The analysis method used is the application of the NDVI algorithm. The main result of this research is that the condition of mangrove density on Pannikiang Island starts from the shallow density class to the very high-density class. Each density class has a different area, each starting from very low density with an area of 49137.98 m², low density with an area of 41947.12 m², medium density with an area of 65916.9 m², high density with an area of 175578.60 m², and very high density with an area of 749854.47 m². This research concludes that mangrove density conditions on Pannikiang Island have five density classes ranging from very low to very high density. This study has important implications for the management and protection of mangrove areas.

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Published

2024-04-04

How to Cite

Rosalina, D., Sabilah, A. A., Rombe, K. H., & Warni. (2024). Mapping of Mangrove Conditions Using Sentinel-2 Imagery. JST (Jurnal Sains Dan Teknologi), 13(1), 89–98. https://doi.org/10.23887/jstundiksha.v13i1.65281

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Vol. 13 No. 1 (2024): April

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Copyright (c) 2024 Anisa Aulia Sabilah, Dwi Rosalina, Katarina Hesty Rombe, Warni

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