Application of Remote Sensing for Mapping Vegetation Density Using Normalized Difference Vegetation Index (NDVI) in Langsa City Mangrove Forest

Mangroves are vital coastal ecosystems that thrive in tidal environments and play a crucial role in biodiversity and shoreline protection. This study aims to assess the vegetation density of the Langsa City Mangrove Forest using the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2A satellite imagery and analyzed through Geographic Information System (GIS) tools, particularly ArcGIS. NDVI values were categorized into four classes: very low (-0.15–0.34), low (0.35–0.48), medium (0.49–0.61), and high (0.62–0.83). The spatial analysis revealed that 57.2% of the area (approx. 128.5 ha) exhibited high vegetation density, while 24.6% (55.2 ha) showed medium density, and 13.3% (29.9 ha) had low vegetation. Approximately 4.9% (11.0 ha) of the area was classified as very low density, indicating regions with potential for ecological rehabilitation. These findings demonstrate that NDVI is an effective and reliable indicator for monitoring mangrove vegetation health. Routine application of NDVI analysis is essential for supporting sustainable management strategies and long-term conservation planning in coastal forest ecosystems..

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Journal
Jurnal Penelitian Pendidikan IPA
Published
2025-07-25
DOI
https://doi.org/10.29303/jppipa.v11i7.11530
Primary Topic
Agricultural and Environmental Management
Type
article
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article

Application of Remote Sensing for Mapping Vegetation Density Using Normalized Difference Vegetation Index (NDVI) in Langsa City Mangrove Forest

Saida Rasnovi, Dahlan Dahlan, Fuji Attariq Unsha
Jurnal Penelitian Pendidikan IPA
Agricultural and Environmental Management
article

Application of Remote Sensing for Mapping Vegetation Density Using Normalized Difference Vegetation Index (NDVI) in Langsa City Mangrove Forest

Saida Rasnovi, Dahlan Dahlan, Fuji Attariq Unsha
article en

Abstract

Mangroves are vital coastal ecosystems that thrive in tidal environments and play a crucial role in biodiversity and shoreline protection. This study aims to assess the vegetation density of the Langsa City Mangrove Forest using the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2A satellite imagery and analyzed through Geographic Information System (GIS) tools, particularly ArcGIS. NDVI values were categorized into four classes: very low (-0.15–0.34), low (0.35–0.48), medium (0.49–0.61), and high (0.62–0.83). The spatial analysis revealed that 57.2% of the area (approx. 128.5 ha) exhibited high vegetation density, while 24.6% (55.2 ha) showed medium density, and 13.3% (29.9 ha) had low vegetation. Approximately 4.9% (11.0 ha) of the area was classified as very low density, indicating regions with potential for ecological rehabilitation. These findings demonstrate that NDVI is an effective and reliable indicator for monitoring mangrove vegetation health. Routine application of NDVI analysis is essential for supporting sustainable management strategies and long-term conservation planning in coastal forest ecosystems..

Jurnal Penelitian Pendidikan IPAVol. 11(7)
Universitas Syiah Kuala (ID)
Life in Land
Openalex Percentile: Top 63%
Agricultural and Environmental Management
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