Analysis and Identification of Landuse on the Coastal Environment of South Sumatra using GIS

Yuanita Windusari Soedarto (1), Laila Hanum (2), Margareta Sri Lestari (3)
(1) Biology Department, Mathematic and Natural Sciences Faculty, Sriwijaya University, South Sumatra, Indonesia
(2) Biology Department, Mathematic and Natural Sciences Faculty, Sriwijaya University, South Sumatra, Indonesia
(3) Biology Department, Mathematic and Natural Sciences Faculty, Sriwijaya University, South Sumatra, Indonesia
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How to cite (IJASEIT) :
Soedarto, Yuanita Windusari, et al. “Analysis and Identification of Landuse on the Coastal Environment of South Sumatra Using GIS”. International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 3, June 2017, pp. 785-91, doi:10.18517/ijaseit.7.3.2223.
Analysis and identification of land use in coastal areas to study the coastal environment Sembilang National Park in South Sumatra using remote sensing system (Geographical Information System) has been conducted from June until November 2014. The objective to study the changes that occur in the coastal environment as well as to identify and estimate the area use change existing mangrove areas in Region I of the Section of Sembilang National Park Management, South Sumatra. Methods for the analysis and identification based on Landsat image data 8 in 2013 using ENVI 4.3 and Arc GIS 9.3 software as well as the conversion of ground check. The results showed the use of land in the mangrove areas in the region I of the Section of Sembilang National Park Management classified into 5 classes, namely mangrove, water area, mangrove shrubs, mainland mud, and ponds areas. The area of each class were observed in sequence as follows 8921.19 ha (41.69%) as mangrove area; 3934.3 ha (23.28%) as water areas; 3.608,52 ha (17.41%) as area of mangrove shrubs; 1.649,11 ha (9.05%) as mainland mud and settlement area; and 1.561,04 ha (8.57%) as the ponds area. The percentage of the class obtained as a result of the conversion of ground check, and it is based on the land use map data over the total area observed.

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