Mangrove forest is a susceptive ecosystem which needs continuous monitoring to detect various threats such as human activities and natural disasters. Remote sensing and geographical information system (GIS) are very effective tools to be used in monitoring mangrove ecosystem due to they can reach large areas and periodically. Application of remote sensing technology to monitor mangrove ecosystem in Sebatik Island had never been conducted before. This research is important to be carried out to reveal changes in condition of mangrove forest in Sebatik Island. Aims of this research were analyzing the correlation between Normalized Different Vegetation Index (NDVI) values and its canopy cover percentages, calculated the accuracy of land cover classification with different spatial resolution, and measuring the changes of mangrove covers from 2005 to 2016. Land cover classification in this research used supervised classification with Maximum Likelihood algorithm. The NDVI was used as mangrove density indicator and vegetation condition. Field data measurement was taken to count canopy cover. The accuracy of Landsat images classification was about 83% and the SPOT 6 images around of 90%. Mangrove forest in Sebatik Island had increased from 2005 to 2016 as high as 31.27%. The correlation between NDVI and canopy percent cover were categorized as high with their coeficient correlation r=0.82 (Landsat 8) and 0.85 (SPOT 6).
ABSTRAKHutan mangrove merupakan ekosistem yang rentan sehingga membutuhkan pemantauan terus menerus untuk mendeteksi berbagai ancaman seperti aktivitas manusia dan bencana alam. Pengindraan jauh dan sistem informasi geografis (SIG) merupakan alat yang sangat efektif untuk digunakan dalam pemantauan ekosistem mangrove karena dapat menjangkau daerah yang luas dan dapat dilakukan sekala berkala. Penerapan teknologi pengindraan jauh untuk memantau ekosistem mangrove di Pulau Sebatik belum pernah dilakukan sebelumnya. Penelitian ini penting untuk mengetahui perubahan kondisi hutan mangrove di Pulau Sebatik. Tujuan dari penelitian ini adalah menganalisis korelasi antara nilai Normalized Different Vegetation Index (NDVI) dan persentase tutupan kanopi mangrove, menghitung akurasi klasifikasi tutupan lahan dengan resolusi spasial yang berbeda, dan mengukur perubahan sebaran mangrove dari tahun 2005 sampai 2016. Klasifikasi tutupan lahan dalam penelitian ini menggunakan klasifikasi terbimbing dengan algoritma Maximum Likelihood. NDVI digunakan sebagai indikator kerapatan tutupan mangrove. Pengukuran data lapangan diambil untuk menghitung tutupan kanopi. Penilaian akurasi klasifikasi citra Landsat sekitar 83% dan citra SPOT 6 sekitar 90%. Mangrove di Pulau Sebatik mengalami peningkatan dari tahun 2005 sampai 2016 sebesar 31,27%. Korelasi antara NDVI dan tutupan kanopi dikategorikan tinggi dengan koefisien korelasi r = 0,82 (Landsat 8) dan 0,85 (SPOT 6).
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