IDENTIFICATION OF MANGROVE FORESTS USING MULTISPECTRAL SATELLITE IMAGERIES

Authors

  • Anang Dwi Purwanto Remote Sensing Applications Center, National Institute of Aeronautics and Space
  • Wikanti Asriningrum Remote Sensing Applications Center, National Institute of Aeronautics and Space

DOI:

https://doi.org/10.30536/j.ijreses.2019.v16.a3097

Keywords:

Mangrove, OIF, Landsat 8, Sentinel 2A, SPOT 6, Combinations

Abstract

The visual identification of mangrove forests is greatly constrained by combinations of RGB composite. This research aims to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using the Optimum Index Factor (OIF) method. The OIF method uses the standard deviation value and correlation coefficient from a combination of three image bands. The image data comprise Landsat 8 imagery acquired on 30 May 2013, Sentinel 2A imagery acquired on 18 March 2018 and images from SPOT 6 acquired on 10 January 2015. The results show that the band composites of 564 (NIR+SWIR+Red) from Landsat 8 and 8a114 (Vegetation Red Edge+SWIR+Red) from Sentinel 2A are the best RGB composites for identifying mangrove forest, in addition to those of 341 (Red+NIR+Blue) from SPOT 6. The near-infrared (NIR) and short-wave infrared (SWIR) bands play an important role in determining mangrove forests. The properties of vegetation are reflected strongly at the NIR wavelength and the SWIR band is very sensitive to evaporation and the identification of wetlands.

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Published

2025-11-25

Issue

Vol. 16 No. 1 (2019)

Section

Articles

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Copyright (c) 2019 Author (s)

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