| dc.description.abstract | Mangrove memiliki peran penting dalam menjaga keseimbangan ekosistem pesisir dan juga memberikan manfaat ekonomi bagi masyarakat sekitar. Penelitian ini bertujuan untuk membandingkan penggunaan metode Normalized Difference Vegetation Index (NDVI) dan Enhanced Vegetation Index (EVI) dalam pemetaan kerapatan vegetasi mangrove di Pulau Lancang menggunakan citra Sentinel-2A. Algoritma yang digunakan, yaitu algoritma Mangrove Vegetation Index (MVI) untuk membedakan vegetasi mangrove dan bukan mangrove, serta algoritma Normalized Difference Vegetation Index (NDVI) dan Enhanced Vegetation Index (EVI) untuk memetakan kerapatan mangrove. Klasifikasi kerapatan mangrove menggunakan metode NDVI menghasilkan 3 kelas, yaitu jarang (2,00 ha), sedang (1,00 ha), dan rapat (11,05 ha). Sedangkan klasifikasi kerapatan menggunakan EVI hanya menghasilkan 2 kelas, yaitu jarang (10,38 ha) dan sedang (3,67 ha). Uji korelasi antara data lapang tutupan kanopi mangrove dengan nilai NDVI dan EVI menghasilkan nilai koefisien korelasi (r) sebesar 0,85 dan 0,83 serta nilai koefisien determinasi (R2) sebesar 0,72 dan 0,69. Uji akurasi menggunakan metode confusion matrix terhadap kerapatan mangrove menghasilkan nilai Overall Accuracy (OA) sebesar 81% dengan nilai koefisien kappa sebesar 0,88. | |
| dc.description.abstract | Mangrove plays a vital role in maintaining the balance of coastal ecosystems and provides economic benefits to local communities. This study aims to compare the use of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) in mapping mangrove vegetation density on Lancang Island using Sentinel-2A imagery. Algorithms were used: the Mangrove Vegetation Index (MVI) to differentiate mangrove vegetation from non-mangrove vegetation, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) to map mangrove density. Classification of mangrove density using the NDVI method resulted in three classes: sparse (2.00 ha), moderate (1.00 ha), and dense (11.05 ha), while the classification of density using EVI only resulted in two classes: sparse (10.38 ha) and moderate (3.67 ha). Correlation tests between field data on mangrove canopy cover, NDVI, and EVI values resulted in correlation coefficients (r) of 0.85 and 0.83 and coefficients of determination (R²) of 0.72 and 0.69. Accuracy testing using the confusion matrix method for mangrove density resulted in an Overall Accuracy (OA) of 81% with a kappa coefficient of 0.88. | |
