Pemetaan Sebaran dan Kerapatan Mangrove Menggunakan Sentinel-2A di Desa Sukajaya, Kabupaten Karawang

Abstract

Indonesia sebagai negara tropis memiliki kondisi ideal bagi pertumbuhan mangrove yang berperan penting secara fisik, ekologis, dan sosial ekonomi. Penelitian ini bertujuan memetakan sebaran dan kerapatan mangrove di Desa Sukajaya, Kabupaten Karawang tahun 2025 menggunakan citra Sentinel-2A. Klasifikasi mangrove dilakukan menggunakan algoritma Mangrove Vegetation Index (MVI) dan Enhanced Mangrove Index (EMI). Hasil klasifikasi terbaik selanjutnya digunakan untuk analisis kerapatan mangrove menggunakan Normalized Difference Vegetation Index (NDVI) dan melihat korelasi antara nilai NDVI dengan persentase tutupan kanopi yang diperoleh menggunakan metode hemispherical photography. Hasil penelitian menunjukkan bahwa MVI memiliki akurasi tertinggi dalam memisahkan mangrove dan non mangrove dengan nilai akurasi 94%. NDVI menunjukkan korelasi kuat (r = 0,9051) terhadap tutupan kanopi mangrove. Sebaran mangrove di Desa Sukajaya mengikuti garis pantai yang berbatasan dengan Laut Jawa dan aliran sungai ke arah daratan memiliki luas 33,6 ha yang didominasi kelas kerapatan padat. Penelitian ini diharapkan menjadi acuan pengelolaan pesisir Desa Sukajaya secara berkelanjutan.

As a tropical country, Indonesia offers ideal conditions for mangrove growth, which plays a crucial role in physical, ecological, and socioeconomic terms. This study aims to map the distribution and density of mangroves in Sukajaya Village, Karawang Regency, using Sentinel-2A satellite imagery acquired in 2025. Mangrove classification was performed using the Mangrove Vegetation Index (MVI) and Enhanced Mangrove Index (EMI) algorithms. The best classification result was subsequently used to analyze mangrove density using the Normalized Difference Vegetation Index (NDVI) and to examine the correlation between NDVI values and canopy cover percentage obtained through the hemispherical photography method. The results showed that MVI achieved the highest accuracy in distinguishing mangrove from non-mangrove areas, achieving an overall accuracy of 94%. NDVI exhibited a strong correlation (r = 0.9051) with mangrove canopy cover. Mangrove distribution in Sukajaya Village followed the coastline bordering the Java Sea and extended along river channels inland, covering an area of 33.6 ha, predominantly classified as dense mangrove. The findings of this study are expected to serve as a reference for the sustainable coastal management of Sukajaya Village.