Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove Forests
This study aims to examine the k-means clustering and region growing segmentation methods to identify and measure the area of mangrove forests in the Southeast Sulawesi province. The image of the area of this study used Landsat 8 satellite imagery. The area of mangrove forest was carried out by calc...
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Format: | Article |
Language: | English |
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Diponegoro University
2019-01-01
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Series: | Jurnal Teknologi dan Sistem Komputer |
Subjects: | |
Online Access: | https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13145 |
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author | Tyas Panorama Nan Cerah Oky Dwi Nurhayati R. Rizal Isnanto |
author_facet | Tyas Panorama Nan Cerah Oky Dwi Nurhayati R. Rizal Isnanto |
author_sort | Tyas Panorama Nan Cerah |
collection | DOAJ |
description | This study aims to examine the k-means clustering and region growing segmentation methods to identify and measure the area of mangrove forests in the Southeast Sulawesi province. The image of the area of this study used Landsat 8 satellite imagery. The area of mangrove forest was carried out by calculating the number of pixels identified as mangrove forests with an area density of 900 m2/pixel. The accuracy of the two segmentation methods in calculating the area was compared based on the same area calculated by LAPAN. The overall accuracy of k-means clustering segmentation method has better accuracy, which is 59.26%, than region growing with 33.33% of accuracy. Both image segmentation methods, k-means clustering and region growing, can be used to calculate the area of mangrove forests in the Southeast Sulawesi region using Landsat 8 satellite imagery. |
first_indexed | 2024-03-07T17:46:57Z |
format | Article |
id | doaj.art-6647e734fdd94436ad7a8c04a9cb1281 |
institution | Directory Open Access Journal |
issn | 2338-0403 |
language | English |
last_indexed | 2024-03-07T17:46:57Z |
publishDate | 2019-01-01 |
publisher | Diponegoro University |
record_format | Article |
series | Jurnal Teknologi dan Sistem Komputer |
spelling | doaj.art-6647e734fdd94436ad7a8c04a9cb12812024-03-02T14:51:53ZengDiponegoro UniversityJurnal Teknologi dan Sistem Komputer2338-04032019-01-0171313710.14710/jtsiskom.7.1.2019.31-3712768Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove ForestsTyas Panorama Nan Cerah0Oky Dwi Nurhayati1R. Rizal Isnanto2https://orcid.org/0000-0002-6044-0644Departemen Teknik Komputer, Universitas Diponegoro, IndonesiaDepartemen Teknik Komputer, Universitas Diponegoro, IndonesiaDepartemen Teknik Komputer, Universitas Diponegoro, IndonesiaThis study aims to examine the k-means clustering and region growing segmentation methods to identify and measure the area of mangrove forests in the Southeast Sulawesi province. The image of the area of this study used Landsat 8 satellite imagery. The area of mangrove forest was carried out by calculating the number of pixels identified as mangrove forests with an area density of 900 m2/pixel. The accuracy of the two segmentation methods in calculating the area was compared based on the same area calculated by LAPAN. The overall accuracy of k-means clustering segmentation method has better accuracy, which is 59.26%, than region growing with 33.33% of accuracy. Both image segmentation methods, k-means clustering and region growing, can be used to calculate the area of mangrove forests in the Southeast Sulawesi region using Landsat 8 satellite imagery.https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13145luas hutan mangrovepengolahan citra digitalk-means clusteringregion growingsegmentasi citra satelit |
spellingShingle | Tyas Panorama Nan Cerah Oky Dwi Nurhayati R. Rizal Isnanto Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove Forests Jurnal Teknologi dan Sistem Komputer luas hutan mangrove pengolahan citra digital k-means clustering region growing segmentasi citra satelit |
title | Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove Forests |
title_full | Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove Forests |
title_fullStr | Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove Forests |
title_full_unstemmed | Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove Forests |
title_short | Comparison of K-Means Clustering and Growing Region Segmentation Methods for Area Measurement of Mangrove Forests |
title_sort | comparison of k means clustering and growing region segmentation methods for area measurement of mangrove forests |
topic | luas hutan mangrove pengolahan citra digital k-means clustering region growing segmentasi citra satelit |
url | https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13145 |
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