IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINE

Mapping the distribution of mangrove forests is very important to determine the ecological changes, because mangroves protect biodiversity. Google Earth Engine (GEE) is a cloud-based platform that can analyse the distribution of mangrove forests in a complex and efficient manner. This study aims to...

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Main Authors: Rina Mawardah Batubara, M Taufik Rahmadi, Meilinda Suriani Harefa, Darwin Parlaungan Lubis, Sendi Permana, Rifqi Ulfatun Nikmah, Alvin Pratama
Format: Article
Language:English
Published: Faculty of Teacher Training and Education, Universitas Sebelas Maret 2025-07-01
Series:GeoEco
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Online Access:https://jurnal.uns.ac.id/GeoEco/article/view/99525
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author Rina Mawardah Batubara
M Taufik Rahmadi
Meilinda Suriani Harefa
Darwin Parlaungan Lubis
Sendi Permana
Rifqi Ulfatun Nikmah
Alvin Pratama
author_facet Rina Mawardah Batubara
M Taufik Rahmadi
Meilinda Suriani Harefa
Darwin Parlaungan Lubis
Sendi Permana
Rifqi Ulfatun Nikmah
Alvin Pratama
author_sort Rina Mawardah Batubara
collection DOAJ
description Mapping the distribution of mangrove forests is very important to determine the ecological changes, because mangroves protect biodiversity. Google Earth Engine (GEE) is a cloud-based platform that can analyse the distribution of mangrove forests in a complex and efficient manner. This study aims to analyse the use of Google Earth Engine in monitoring changes in the distribution of mangrove forests in Langkat Regency from 2018 to 2024. This study uses Sentinel-2A image data by applying NDVI computed on Google Earth Engine (GEE). The results of the study show that there has been a change in the distribution of mangrove forests from 27,095.4 Ha (2018) to 26,700.56 Ha (2021) and to 24,685.74 Ha (2024), which shows a reduction in distribution by 394.84 Ha (2018-2021) and 2,014.82 Ha (2021-2024). The largest change in distribution occurred in Pangkalan Susu District with a reduction in area of 307.99 Ha (2021) and 984.64 Ha (2024). Changes in the distribution of mangrove forests are caused by human activities in land clearing for ponds and oil palm plantations. The accuracy test of the Sentinel-2A image uses a Confusion Matrix with an Overall Accuracy of 85%. This study shows the potential that Google Earth Engine-based Citra Sentinel-2A data can be used to monitor the distribution of mangrove forests.
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institution Kabale University
issn 2460-0768
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language English
publishDate 2025-07-01
publisher Faculty of Teacher Training and Education, Universitas Sebelas Maret
record_format Article
series GeoEco
spelling doaj-art-2c06cef3202c495c9dac2665b473e77c2025-08-20T03:43:54ZengFaculty of Teacher Training and Education, Universitas Sebelas MaretGeoEco2460-07682597-60442025-07-0111259360810.20961/ge.v11i2.9952546493IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINERina Mawardah Batubara0M Taufik Rahmadi1Meilinda Suriani Harefa2Darwin Parlaungan Lubis3Sendi Permana4Rifqi Ulfatun Nikmah5Alvin Pratama6Department of Geography Education, Faculty of Social Sciences, Universitas Negeri MedanGeographic Information Science Study Program, Faculty of Social Sciences, Universitas Negeri MedanDepartment of Geography Education, Faculty of Social Sciences, Universitas Negeri MedanGeographic Information Science Study Program, Faculty of Social Sciences, Universitas Negeri MedanDepartment of Geography Education, Faculty of Social Sciences, Universitas Negeri MedanYayasan Konservasi Pesisir IndonesiaDepartment of Geography Education, Faculty of Social Sciences, Universitas Negeri MedanMapping the distribution of mangrove forests is very important to determine the ecological changes, because mangroves protect biodiversity. Google Earth Engine (GEE) is a cloud-based platform that can analyse the distribution of mangrove forests in a complex and efficient manner. This study aims to analyse the use of Google Earth Engine in monitoring changes in the distribution of mangrove forests in Langkat Regency from 2018 to 2024. This study uses Sentinel-2A image data by applying NDVI computed on Google Earth Engine (GEE). The results of the study show that there has been a change in the distribution of mangrove forests from 27,095.4 Ha (2018) to 26,700.56 Ha (2021) and to 24,685.74 Ha (2024), which shows a reduction in distribution by 394.84 Ha (2018-2021) and 2,014.82 Ha (2021-2024). The largest change in distribution occurred in Pangkalan Susu District with a reduction in area of 307.99 Ha (2021) and 984.64 Ha (2024). Changes in the distribution of mangrove forests are caused by human activities in land clearing for ponds and oil palm plantations. The accuracy test of the Sentinel-2A image uses a Confusion Matrix with an Overall Accuracy of 85%. This study shows the potential that Google Earth Engine-based Citra Sentinel-2A data can be used to monitor the distribution of mangrove forests.https://jurnal.uns.ac.id/GeoEco/article/view/99525distributiongoogle earth enginelangkatmangrove forestsentine-2a
spellingShingle Rina Mawardah Batubara
M Taufik Rahmadi
Meilinda Suriani Harefa
Darwin Parlaungan Lubis
Sendi Permana
Rifqi Ulfatun Nikmah
Alvin Pratama
IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINE
GeoEco
distribution
google earth engine
langkat
mangrove forest
sentine-2a
title IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINE
title_full IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINE
title_fullStr IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINE
title_full_unstemmed IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINE
title_short IDENTIFYING CHANGES IN MANGROVE FOREST DISTRIBUTION IN LANGKAT REGENCY USING GOOGLE EARTH ENGINE
title_sort identifying changes in mangrove forest distribution in langkat regency using google earth engine
topic distribution
google earth engine
langkat
mangrove forest
sentine-2a
url https://jurnal.uns.ac.id/GeoEco/article/view/99525
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