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All Journal AL KAUNIYAH Jurnal Penelitian Pendidikan IPA (JPPIPA)
Unsha, Fuji Attariq
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Physics

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Application of Remote Sensing for Mapping Vegetation Density Using Normalized Difference Vegetation Index (NDVI) in Langsa City Mangrove Forest Unsha, Fuji Attariq; Rasnovi, Saida; Dahlan
Jurnal Penelitian Pendidikan IPA Vol 11 No 7 (2025): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i7.11530

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..
Spatial Analysis of Vegetation Density in Langsa City Using NDVI Index Unsha, Fuji Attariq; Rasnovi, Saida; Dahlan
Al-Kauniyah: Jurnal Biologi Vol. 19 No. 1 (2026): AL-KAUNIYAH JURNAL BIOLOGI
Publisher : Department of Biology, Faculty of Science and Technology, Syarif Hidayatullah State Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/kauniyah.v19i1.44468

Abstract

This study aims to analyze the distribution of vegetation density in Langsa City using the Normalized Difference Vegetation Index (NDVI). The research was conducted from June to October 2024, covering a study area of ​​21,881.41 ha. The method used is remote sensing, using Sentinel-2A satellite imagery, along with Geographic Information System (GIS) software, specifically ArcGIS, for mapping and spatial analysis. The NDVI classification results show five land cover categories based on NDVI value ranges. NDVI Class 1 (-0.38 to -0.02) includes non-vegetated land and water bodies. NDVI Class 2 (-0.02–0.20) indicates very low greenness, typically consisting of bare land. NDVI Class 3 (0.20–0.38) represents low greenness, which includes built-up areas. NDVI Class 4 (0.38–0.54) includes moderate greenness, typically found in plantations or fields, while NDVI Class 5 (0.54–0.83) represents high greenness, covering areas such as shrubs, forests, and mangroves. This analysis provides valuable information for land use planning and environmental management based on spatial vegetation data. The results of this study are expected to serve as a basis for policy-making that supports the sustainable management and conservation of vegetation in Langsa City.
Co-Authors Dahlan Saida Rasnovi