Integrasi SIG Dan Penginderaan Jauh Untuk Pemetaan Kesehatan Perkebunan Kelapa Sawit
Studi Kasus: Kecamatan Sangir Balai Janggo, Kabupaten Solok Selatan, Sumatera Barat
DOI:
https://doi.org/10.59061/jsit.v8i1.922Keywords:
Oil Palm Plant Health, NDVI, Remote Sensing, Geographic Information SystemAbstract
Sangir Balai Janggo District has many productive oil palm plantations, making it an ideal location for research related to oil palm plant health. Oil palm is a major commodity in Indonesian plantations, so mapping its health is crucial for sustainable agricultural management. This study aims to analyze the health of oil palm plants using the integration of Geographic Information Systems (GIS) and Remote Sensing with the Normalized Difference Vegetation Index (NDVI) method based on Sentinel-2A imagery. The results of the study show that the health of oil palm plants in Sangir Balai Janggo District is divided into four categories: very healthy (26,967.40 Ha; NDVI 0.66-0.87), fairly healthy (3,228.31 Ha; NDVI 0.33-0.66), unhealthy (547.75 Ha; NDVI 0-0.33), and dead (10.53 Ha; NDVI -0.33 - 0). The total area of oil palm plantations reaches 30,753.62 Ha. This study demonstrates that the integration of GIS and remote sensing is highly effective in accurately and efficiently mapping the health condition of oil palm plantations.
References
Aini, A. (2007). Sistem informasi: Pengertian dan aplikasinya. Angewandte Chemie International Edition, 6(11), 951–952.
Ardiyansyah, M., & Muid, A. (2023). Analisis citra Sentinel-2 dengan metode Normalized Difference Vegetation Index untuk mengetahui ketersediaan ruang terbuka hijau di Kota Bandar Lampung tahun 2022. https://www.ncbi.nlm.nih.gov/books/NBK558907/
Badan Pusat Statistik. (2022). Kecamatan Sangir Balai Janggo.
Iii. (2020). Metode penelitian (pp. 24–39). (Aslinya terbit 2017).
Margareta, A. (2022). Distribusi spasial kesehatan tanaman kelapa sawit di PT. Perkebunan Nusantara VII Unit Rejosari, Natar, Kabupaten Lampung Selatan menggunakan citra satelit Sentinel-2 dan citra satelit Landsat 8.
Oktaviani, N., & Kusuma, H. A. (2017). Introduction of Sentinel-2 satellite imagery for marine mapping. Oseana, 42(3), 40–55.
Pangestu, N. H. A., & Banowati, G. (2023). Pemetaan kesehatan kebun kelapa sawit berdasarkan nilai Normalized Difference Vegetation Index (NDVI) menggunakan citra Landsat-8 di Kebun PT. Wanapotensi Guna. Agriprima: Journal of Applied Agricultural Sciences, 7(1), 40–49.
Rangkuti, M. Pemetaan: Metode dan unsurnya. https://fatek.umsu.ac.id/apa-itu-pemetaan-metode-dan-unsurnya/
Serikat Petani Kelapa Sawit (SPKS). (2016). Standar operasional prosedur pengendalian organisme pengganggu tanaman (SOP Agro, pp. 1–26). http://www.spks.or.id/publikasi/buku-standard-operating-procedure-sop-perkebunan-kelapa-sawit-rakyat-bebas-deforestasi/
Sutanto. (1987). Prinsip dasar penginderaan jauh. Panduan Aplikasi Penginderaan Jauh Tingkat Dasar (pp. 1–44).
Universitas Negeri Surabaya (UNESA). (2012). Buku pedoman standar kompetensi lulusan (No. 31, pp. 1–34).
Widyantara. Perbedaan tanaman dan tumbuhan: Ciri dan jenisnya. https://lindungihutan.com/blog/perbedaan-tanaman-dan-tumbuhan
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