Analisis Spasial Deforestasi Kawasan Hutan Konservasi Taman Nasional Kerinci Seblat Akibat Ekspansi Perkebunan Gambir di Kecamatan Sutera Kabupaten Pesisir Selatan
DOI:
https://doi.org/10.58812/jgws.v4i02.3295Kata Kunci:
Hutan Konservasi, Deforestasi, Perkebunan Gambir, Landsat, Prediksi Tutupan LahanAbstrak
Penelitian ini bertujuan menganalisis perubahan tutupan lahan, mengidentifikasi faktor pendorong deforestasi, serta memprediksi kondisi tutupan lahan tahun 2035 di Kecamatan Sutera, Kabupaten Pesisir Selatan. Populasi penelitian mencakup seluruh kawasan seluas 35.923,53 ha sebagai wilayah penyangga konservasi, dengan sampel 5.000 titik purposive sampling berbasis citra Landsat multitemporal tahun 2005, 2015, dan 2025. Analisis data menggunakan klasifikasi Maximum Likelihood, uji akurasi Confusion Matrix, analisis Euclidean Distance, serta pemodelan Artificial Neural Network melalui plugin MOLUSCE pada QGIS. Hasil menunjukkan penurunan tutupan hutan sebesar 3.272,06 ha (9,11%), dengan ekspansi perkebunan gambir sebagai faktor dominan deforestasi. Prediksi tahun 2035 memperkirakan tutupan hutan menurun hingga 85,71% dari total wilayah. Kebaruan penelitian terletak pada integrasi model ANN-CA untuk prediksi deforestasi berbasis komoditas gambir. Temuan ini menjadi dasar pengelolaan kawasan konservasi dan mitigasi deforestasi secara berkelanjutan.
Referensi
Austin, K. G., Schwantes, A., Gu, Y., & Kasibhatla, P. S. (2019). What causes deforestation in Indonesia? Environmental Research Letters, 14(2), 024007. https://doi.org/10.1088/1748-9326/aaf6db
Belgiu, M., & Drăguț, L. (2016). Random forest in remote sensing: A review of applications and future directions. ISPRS Journal of Photogrammetry and Remote Sensing, 114, 24–31. https://doi.org/10.1016/j.isprsjprs.2016.01.011
Clarke, K. C., Hoppen, S., & Gaydos, L. (1997). A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B: Planning and Design, *24*(2), 247–261. https://doi.org/10.1068/b240247
Congalton, R. G., & Green, K. (2009). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices (2nd ed.). CRC Press. https://doi.org/10.1201/9781420055139
Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., & Lambin, E. (2004). Digital change detection methods in ecosystem monitoring: A review. International Journal of Remote Sensing, 25(9), 1565–1596. https://doi.org/10.1080/0143116031000101675
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A., & Hansen, M. C. (2018). Classifying drivers of global forest loss. Science, 361(6407), 1108–1111. https://doi.org/10.1126/science.aau3445
Food and Agriculture Organization (FAO). (2020). Global Forest Resources Assessment 2020. FAO. https://doi.org/10.4060/ca9825en
Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, *80*(1), 185–201. https://doi.org/10.1016/S0034-4257(01)00295-4
Gaveau, D. L. A., Sheil, D., Husnayaen, Salim, M. A., Arjasakusuma, S., Ancrenaz, M., Pacheco, P., & Meijaard, E. (2016). Rapid conversions and avoided deforestation: Examining four decades of industrial plantation expansion in Borneo. Scientific Reports, *6*, 32017. https://doi.org/10.1038/srep32017
Gaveau, D. L. A., Locatelli, B., Salim, M. A., Yaen, H., Pacheco, P., & Sheil, D. (2022). Slowing deforestation in Indonesia follows declining oil palm expansion and lower oil prices. PLOS ONE, 17 (3), e0266178. https://doi.org/10.1371/journal.pone.0266178
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., & Townshend, J. R. G. (2013). High-resolution global maps of 21st-century forest cover change. Science, *342*(6160), 850–853. https://doi.org/10.1126/science.1244693
Jensen, J. R. (2016). Introductory Digital Image Processing: A Remote Sensing Perspective (4th ed.). Pearson Education.
Kementerian Lingkungan Hidup dan Kehutanan (KLHK). (2023). Statistik Direktorat Jenderal Planologi Kehutanan dan Tata Lingkungan 2023. KLHK.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310
Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote Sensing and Image Interpretation (7th ed.). John Wiley & Sons.
Lu, D., & Weng, Q. (2007). A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, 28(5), 823–870. https://doi.org/10.1080/01431160600746456
Margono, B. A., Potapov, P. V., Turubanova, S., Stolle, F., & Hansen, M. C. (2014). Primary forest cover loss in Indonesia over 2000–2012. Nature Climate Change, 4(8), 730–735. https://doi.org/10.1038/nclimate2277
Miettinen, J., Shi, C., & Liew, S. C. (2011). Deforestation rates in insular Southeast Asia between 2000 and 2010. Global Change Biology, 17 (7), 2261–2270. https://doi.org/10.1111/j.1365-2486.2011.02398.x
Prasetyo, L. B., Dharmawan, A. H., Nasdian, F. T., & Ramdhoni, S. (2019). Historical forest cover change patterns in Kerinci Seblat National Park: A case of agricultural expansion and forest degradation. Forest and Society, 3 (1), 42–58. https://doi.org/10.24259/fs.v3i1.5619
Rodriguez-Galiano, V. F., Ghimire, B., Rogan, J., Chica-Olmo, M., & Rigol-Sanchez, J. P. (2012). An assessment of the effectiveness of a random forest classifier for land-cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 67, 93–104. https://doi.org/10.1016/j.isprsjprs.2011.11.002
Soares-Filho, B. S., Cerqueira, G. C., & Pennachin, C. L. (2002). DINAMICA—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier. Ecological Modelling, 154 (3), 217–235. https://doi.org/10.1016/S0304-3800(02)00059-5
Sugiyono. (2019). Metode Penelitian Kuantitatif, Kualitatif, dan R&D (Edisi 2). Alfabeta.
UNESCO. (2021). Tropical Rainforest Heritage of Sumatra. UNESCO World Heritage Centre. https://whc.unesco.org/en/list/1167/
World Resources Institute (WRI) Indonesia. (2023). Indonesia Forest and Land Use Update 2023. WRI Indonesia.
World Wide Fund for Nature (WWF) Indonesia. (2022). Status Konservasi Harimau Sumatera dan Habitatnya. WWF Indonesia.
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Hak Cipta (c) 2026 Muhammad Rohif Kurniawan, Arie Yulfa
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