Spatiotemporal dynamics of vegetation density in moramo district protected forest: A remote sensing approach

Authors

  • La Gandri Department of Environmental Science, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • Muhammad Fatahuddin Department of Forestry, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • Sahindomi Bana Department of Forestry, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • Umar Ode Hasani Department of Forestry, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • Abdul Sakti Department of Forestry, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • Dewi Fitriani Department of Forestry, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • La De Ahmaliun Department of Forestry, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • Muhsimin Department of Environmental Science, Faculty of Forestry and Environmental Science, Universitas Halu Oleo, Kendari, Southeast Sulawesi 93231 , Indonesia
  • Vivi Fitriani Department of Soil Science, Faculty of Agriculture, Universitas Jember, Jember, East Java 68121, Indonesia

DOI:

https://doi.org/10.61511/aes.v3i1.2025.1812

Keywords:

Moramo District, protected forest, remote sensing, vegetation density

Abstract

Background: Protected forests in the Moramo District play a critical role in maintaining ecosystem balance, but they are increasingly threatened by human activities such as illegal logging and land use change. Vegetation density shifts can disrupt ecosystem functions, particularly the hydrological cycle. This study aims to analyze spatial and temporal changes in vegetation density in the Moramo District Protected Forest using remote sensing. Methods: To detect vegetation density changes, the NDVI (Normalized Difference Vegetation Index) algorithm was employed using satellite imagery from Landsat OLI 8 (2013 and 2018) and Landsat OLI 9 (2023), processed with GIS software. NDVI values range from -1 to 1, allowing for vegetation condition assessment based on spectral reflectance. Findings: Results show a degradation trend in dense vegetation, with a decrease of 67.25 ha (2.86%) during 2013–2018 and 289.11 ha (12.31%) during 2018–2023. Conversely, moderately dense vegetation increased by 68.45 ha (2.91%) and 300.21 ha (12.78%) over the same periods, indicating signs of vegetation regeneration. Conclusion: Despite some vegetation recovery, forest ecosystems continue to face high pressure. More adaptive conservation strategies supported by spatial monitoring are needed to reduce degradation and support long-term sustainability. Novelty/Originality of this article: This study uniquely integrates a multi-temporal NDVI-based approach with socio-ecological analysis and GIS tools to monitor vegetation dynamics. It offers valuable insights for adaptive forest management in the Moramo District Protected Forest, an area previously lacking detailed environmental change analysis.

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Published

2025-07-30

How to Cite

Gandri, L., Fatahuddin, M., Bana, S., Hasani, U. O., Sakti, A., Fitriani, D., … Fitriani, V. (2025). Spatiotemporal dynamics of vegetation density in moramo district protected forest: A remote sensing approach. Applied Environmental Science, 3(1). https://doi.org/10.61511/aes.v3i1.2025.1812

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Vol. 3 No. 1: (July) 2025

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Copyright (c) 2025 La Gandri, Muhammad Fatahuddin, Sahindomi Bana, Umar Ode Hasani, Abdul Sakti, Dewi Fitriani, La De Ahmaliun, Muhsimin, Vivi Fitriani

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