Mangrove Distribution in Riau Islands Using Remote Sensing Technology

Mangrove Distribution in Riau Islands

  • Sudra Irawan Geomatics Engineering, Politeknik Negeri Batam, Ahmad Yani Street, Batam Centre, 29461, Indonesia.
  • Dwi Ely Kurniawan Informatic Engineering, Politeknik Negeri Batam, Ahmad Yani Street, Batam Centre, 29461, Indonesia.
  • Wenang Anurogo Geomatics Engineering, Politeknik Negeri Batam, Ahmad Yani Street, Batam Centre, 29461, Indonesia.
  • Muhammad Zainuddin Lubis Geomatics Engineering, Politeknik Negeri Batam, Ahmad Yani Street, Batam Centre, 29461, Indonesia.

Abstract

Mangrove mapping is done with remote sensing technology using high-resolution image data. Application and information are then presented in web form. This study aims to map the mangrove distribution in Riau Islands, Indonesia. Based on the analysis, from the research data obtained the total area of mangrove in Riau Islands in 2011 and 2017 amounted to 71,504.83 Ha and 64,218.90 Ha, decreased by 7,285, 93 Ha or decreased by 10.19%. Based on the regency, the largest mangrove area in 2017 is located in Batam City of 22,964.77 Ha, then Karimun Regency (13,659,58 Ha), Lingga Regency (11,881.61 Ha), Regency of Bintan (9,701.49) Ha, Natuna Regency (2,477.16 Ha), Tanjungpinang City (1,847.65 Ha), and Anambas Regency (1,686.61 Ha). The magnitude of the widespread change (widespread reduction) occurring over the years between 2011 and 2017 by district, Natuna Regency experienced the largest reduction of 1,949.69 Ha or around 41.39%, followed by Lingga Regency of 1,947.15 Ha (14.08%), Tanjungpinang Municipality of 284.13 Ha (13.33%), Karimun Regency 1,920.93 Ha (12.33%), Anambas Regency of 195.90 Ha (10.40%), Batam City 1,094.83 Ha (4.55%) and Bintan Regency with 93.29 Ha (0, 95%). Opportunities that the pixels classified on the mangrove image are truly mangrove on the facts in the field.

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Published
2017-08-08
How to Cite
IRAWAN, Sudra et al. Mangrove Distribution in Riau Islands Using Remote Sensing Technology. Journal of Applied Geospatial Information, [S.l.], v. 1, n. 2, p. 58-62, aug. 2017. ISSN 2579-3608. Available at: <http://jurnal.polibatam.ac.id/index.php/JAGI/article/view/456>. Date accessed: 26 sep. 2017.

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