Analysis of Mangrove Vegetation and Distribution Using Landsat 8 Images In Bolaang Mongondow East, North Sulawesi
DOI:
https://doi.org/10.35800/jip.v10i2.41069Keywords:
density, mangrove, Landsat 8, NDVIAbstract
Mangrove is one of the objects that can be identified by remote sensing technology using satellite imagery. Analysis of the distribution and density of mangrove vegetation using Landsat 8 imagery was carried out in Bolaang Mongondow Timur, North Sulawesi in September 2020. This study aims to map the distribution of mangroves and determine the correlation between NDVI values, canopy cover, and mangrove density. The data analysis used Landsat 8 images with ENVI 5.3 and ArcGIS 10.1 software. Maximum likelihood classification is used to separate mangrove and non-mangrove features. The calculation of mangrove vegetation density using the NDVI algorithm and single-channel classification using the density slice method to divide mangrove density based on the range of pixel values of the NDVI image. Next, to test the accuracy of the classification results using an error matrix (confusion matrix) and the NDVI vegetation index correlation test compared with canopy cover and density data. The classification resulted in four different land cover classes with an overall accuracy of 97.70% and a kappa coefficient of 0.9688. The mangrove vegetation distribution from the classification results is 524.75 ha. The NDVI correlation with the percentage of canopy cover is very significant with a correlation coefficient (r) = 0.9516, while the NDVI correlation with density resulted in moderate correlation (r = 0.5315).
Keywords: density; mangrove; Landsat 8; NDVI
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Abstrak
Mangrove merupakan salah satu objek yang dapat diidentifikasi menggunakan teknologi penginderaan jauh yakni memanfaatkan citra satelit. Analisis sebaran dan kerapatan vegetasi mangrove menggunakan citra Landsat 8 telah dilakukan di Bolaang Mongondow Timur, Sulawesi Utara pada bulan September 2020. Penelitian ini bertujuan untuk memetakan sebaran mangrove dan mengetahui hubungan korelasi antara nilai NDVI dengan tutupan kanopi dan kerapatan mangrove. Pengolahan data citra Landsat 8 dengan perangkat lunak ENVI 5.3 dan ArcGIS 10.1. Klasifikasi maximum likelihood digunakan untuk memisahkan fitur mangrove dan non mangrove. Perhitungan kerapatan vegetasi mangrove dengan algoritma NDVI dan klasifikasi saluran tunggal menggunakan metode density slice untuk membagi kerapatan mangrove berdasarkan rentang nilai piksel citra NDVI. Uji akurasi hasil klasifikasi menggunakan matriks kesalahan (confussion matriks) dan uji korelasi indeks vegetasi NDVI dengan data tutupan kanopi dan kerapatan. Hasil klasifikasi mendapatkan empat kelas tutupan lahan yang berbeda dengan overall akurasi sebesar 97,70 % dengan kappa coefisien sebesar 0,9688. Luas sebaran vegetasi mangrove dari hasil klasifikasi adalah 524,75 ha. Korelasi NDVIÂ dengan persentase tutupan kanopi termasuk korelasi sangat kuat dengan koefisien korelasi r = 0,9516 sedangkan korelasi NDVIÂ dengan kerapatan termasuk korelasi sedang (r = 0,5315).
Kata kunci: kerapatan; mangrove; Landsat 8; NDVIÂ
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