Mapping Mangrove Species Distribution and Density Using Sentinel-2 Satellite Imagery and Spectral Analysis

Linear Spectral Unmixing Mangrove Pamurbaya Remote Sensing Sustainability.

Authors

  • Lalu Muhamad Jaelani
    lmjaelani@its.ac.id
    Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111,, Indonesia http://orcid.org/0000-0003-2663-9016
  • Dwi Sugma Safitri Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111,, Indonesia
  • Naomy Elliana Kristian Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111,, Indonesia
  • Aldea Noor Alina Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111,, Indonesia
  • Muhammad Aldila Syariz Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111,, Indonesia
  • Hartanto Sanjaya Research Center for Geoinformatics, National Research and Innovation Agency (BRIN), Jakarta Pusat 10340,, Indonesia
  • Abdul Rauf Abdul Rasam College of Built Environment, Malaysia Institute of Transport, Universiti Teknologi MARA, Shah Alam, Selangor 40450,, Malaysia

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This study aimed to conduct a comprehensive analysis and mapping of mangrove species distribution and density in conservation areas of Surabaya, Indonesia. The investigation focused on assessing the current state of mangrove ecosystems using Sentinel-2 satellite imagery and advanced spectral analysis methods, which were crucial for climate regulation, food security, and poverty reduction. Moreover, Linear Spectral Unmixing (LSU) was used to accurately classify mangrove species and individual densities. The methodology included the use of radiometrically corrected Sentinel-2A imagery and spectral library data obtained from various national agencies. The findings showed that the Pamurbaya protected area covered 7,965,971 m², with Avicennia Marina accounting for 74% of the mangrove, followed by Rhizophora Mucronata (24%) and Rhizophora Apiculata (2%). Additionally, this study showed significant density variations, with 83% of the area densely populated, and also provided novel insights by applying LSU, indicating a significant advancement in environmental monitoring. The outcome offered critical information for policymakers and stakeholders to develop effective conservation and management strategies to ensure the long-term sustainability of critical coastal ecosystems. Finally, the findings showed the urgency of systematic conservation efforts to address the impact of deforestation and land-use changes on mangrove habitats worldwide.

 

Doi: 10.28991/HEF-2025-06-01-01

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