Back to Search Start Over

Pemetaan Distribusi Mangrove Menggunakan Citra Sentinel-2A: Studi Kasus Kota Langsa

Authors :
M Taufik Rahmadi
Eni Yuniastuti
Maulana Abdul Hakim
Ayu Suciani
Source :
Jambura Geoscience Review, Vol 4, Iss 1, Pp 1-10 (2021), Jambura Geoscience Review; Vol 4, No 1 (2022): Jambura Geoscience Review (JGEOSREV); 1-10
Publication Year :
2021
Publisher :
Universitas Negeri Gorontalo - Fakultas Matematika dan IPA, 2021.

Abstract

Mangroves are one of the most productive ecosystems for human life, marine ecosystems, and coastal areas. Mangrove distribution is a distribution based on specific geographical or administrative boundaries. Kota Langsa is one of the areas that has a good representation of the distribution of mangroves. Therefore, researchers studied the Kota Langsa area because Kota Langsa is one of the areas with the largest and most diverse mangrove ecosystem in Aceh Province. This study examines the mapping of mangrove distribution using Sentinel-2A multispectral imagery with composite images of Red, Green, and Blue. This research uses SNAP software. The research stages consist of radiometric correction, atmospheric correction, and multispectral image classification. The method used in image classification is the maximum likelihood algorithm. The use of the maximum likelihood algorithm is because the maximum likelihood algorithm gives the best results among other algorithms. The development of the research is the distribution of mangroves in Langsa City, covering an area of 4727.35 ha, which is divided into three sub-districts and eleven gampong (kelurahan). The sub-districts that have mangrove distribution are East Langsa District covering an area of 3240.25 Ha (68.55%), Langsa Barat District covering an area of 1486.47 Ha (31.45%), and Langsa Lama District covering an area of 0.63 Ha (0.013).

Details

ISSN :
26560380 and 26230682
Volume :
4
Database :
OpenAIRE
Journal :
Jambura Geoscience Review
Accession number :
edsair.doi.dedup.....ce2a488a67ee01a33e45f7569dc5a46c
Full Text :
https://doi.org/10.34312/jgeosrev.v4i1.11380