PRIORITIZING DEGRADED LANDSCAPE REHABILITATION USING NDVI, NBR, FRAGMENTATION, RANDOM FOREST, AND AHP IN BENGKULU PROVINCE
PRIORITAS REHABILITASI LANSKAP TERDEGRADASI BERBASIS NDVI, NBR, FRAGMENTASI, RANDOM FOREST, DAN AHP DI PROVINSI BENGKULU
DOI:
https://doi.org/10.54902/586a1g96Kata Kunci:
landscape rehabilitation, NDVI, landscape fragmentation, spatial planning, Bengkulu ProvinceAbstrak
Landscape degradation caused by declining vegetation quality, habitat fragmentation, and increasing land-use pressure has become a major challenge for sustainable natural resource management in Bengkulu Province, Indonesia. This study aims to identify the level of landscape degradation, analyze the dominant factors influencing degradation, and determine watershed-based rehabilitation priority areas. The analysis utilized Sentinel-2 and Landsat imagery from 2015-2025 integrated with slope, road network, watershed (DAS), Regional Spatial Planning (RTRW), and flood and landslide risk data. Landscape degradation was assessed using the Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and landscape fragmentation metrics. Random Forest analysis was employed to identify dominant factors (Overall Accuracy = 89.2%, Kappa = 0.87), while the Analytical Hierarchy Process (AHP) was applied to establish rehabilitation priorities (CR = 0.068). The results indicate that approximately 156,000 ha (7.8%) of Bengkulu Province are classified as degraded to highly degraded, with a Fragmentation Index value of 0.65, indicating a high level of landscape fragmentation. Random Forest analysis revealed that vegetation condition, landscape fragmentation, and road accessibility were the most influential factors driving degradation. Spatial analysis showed that degraded areas tend to be concentrated near road networks and in areas inconsistent with regional spatial planning. The integration of all indicators identified 129,800 ha as high to very high rehabilitation priority areas, primarily located within the Air Bengkulu, Ketahun, and Seluma watersheds. These findings demonstrate that an integrated approach combining NDVI, NBR, landscape fragmentation, Random Forest, and AHP provides a comprehensive scientific basis for landscape rehabilitation planning and sustainable spatial management in Bengkulu Province.
Unduhan
Referensi
Ardiansyah, M., & Suryadi, A. (2021). Analisis Perubahan Tutupan Lahan Berbasis NDVI Menggunakan Citra Landsat di Wilayah Tropis. Jurnal Geografi Lingkungan, 19(2), 115–126.
Arifin, S., Kartika, T., Dirgahayu, D., & Nugroho, G. (2020). Monitoring Model of Land Cover Change for the Indication of Devegetation and Revegetation Using Sentinel-2. International Journal of Remote Sensing and Earth Sciences, 17(2), 93–106.
Badan Informasi Geospasial. (2022). DEMNAS (Digital Elevation Model Nasional) Indonesia. BIG.
BNPB. (2021). InaRISK: Indonesia Disaster Risk Information System. Badan Nasional Penanggulangan Bencana.
Copernicus Programme. (2023). Sentinel-2 User Guide and Data Products. European Space Agency. https://sentinel.esa.int/
FAO. (2020). Global Forest Resources Assessment 2020. Food and Agriculture Organization of the United Nations.
Haddad, N. M., Brudvig, L. A., Clobert, J., Davies, K. F., Gonzalez, A., Holt, R. D., Lovejoy, T. E., Sexton, J. O., Austin, M. P., Collins, C. D., Cook, W. M., Damschen, E. I., Ewers, R. M., Foster, B. L., Jenkins, C. N., King, A., Laurance, W. F., Levey, D. J., Margules, C. R., Townshend, J. R. (2019). Habitat Fragmentation and its Lasting Impact on Earth’s ecosystems. Science Advances, 5(7), eaax8992.
Hidayat, F., Wijaya, A., & Ramdani, F. (2023). Pemanfaatan Random Forest untuk Identifikasi Faktor Perubahan Tutupan lahan di Indonesia. Jurnal Geografi Indonesia, 15(2), 87–99.
Julianto, F. D., Putri, D. P. D., & Safi'i, H. H. (2022). Analisis Perubahan Vegetasi Dengan Data Sentinel-2 Menggunakan Google Earth Engine (Studi Kasus Provinsi Daerah Istimewa Yogyakarta). Jurnal Penginderaan Jauh Indonesia, 2(2), 13–18.
Kementerian Lingkungan Hidup dan Kehutanan (KLHK). (2023). Data dan Informasi Rehabilitasi Hutan dan Lahan Indonesia. Jakarta: KLHK.
Lasaponara, R., Lanorte, A., & Estes, L. (2018). Vegetation Dynamics Assessment Using NDVI Time Series in Tropical Regions. Remote Sensing, 10(4), 567.
Laurance, W. F., Campbell, M. J., Alamgir, M., & Mahmoud, M. I. (2018). Road Expansion and the Fate of Africa’s Tropical Forests. Frontiers in Ecology and Evolution, 6, 75.
Laurance, W. F., Sloan, S., Weng, L., & Sayer, J. A. (2018). Estimating the Environmental Costs of Forest Loss and Degradation. Science Advances, 4(10), eaar2860
Nadzirah, R., Rizqon, M. K., & Indarto. (2023). Application of Sentinel-2A Images for Land Cover Classification Using NDVI in Jember Regency. Geosfera Indonesia, 9(1), 1–15.
Pratama, R., Syartinilia, & Baskoro, D. (2021). Pengaruh Jaringan Jalan Terhadap Perubahan Penggunaan Lahan di Wilayah Hutan Tropis Indonesia. Jurnal Tanah dan Iklim, 45(2), 101–113.
Putra, A., Kuswantoro, D., & Nugroho, B. (2022). Analisis Fragmentasi Lanskap Hutan Tropis Menggunakan Metrik Spasial. Jurnal Sylva Lestari, 10(2), 145–156.
Rahman, A., Kurniawan, B., & Yulianti, D. (2024). Prioritas Rehabilitasi DAS Berbasis Analisis Spasial untuk Mendukung Pengelolaan Sumber Daya Air Berkelanjutan. Jurnal Wilayah dan Lingkungan, 12(1), 35–49.
Rahmawati, S. D., & Apriyanti, D. (2023). Klasifikasi Area Vegetasi dan Non Vegetasi Pada Citra Sentinel-2 Menggunakan Metode EVI dengan Google Earth Engine (Studi Kasus: Kabupaten Klaten). Jurnal Ilmiah Geomatika, 3(1), 1–13.
Reed, J., Ickowitz, A., Chervier, C., et al. (2020). Integrated Landscape Approaches in the Tropics. Land Use Policy, 99, 104822.
Saaty, T. L., & Vargas, L. G. (2021). The Analytic Hierarchy Process: Advances in Decision Making and Applications. RWS Publications.
Siregar, R., Harini, R., & Suharyadi. (2021). Analisis Hotspot Perubahan Penggunaan Lahan Menggunakan Metode Kernel Density. Majalah Geografi Indonesia, 35(2), 110–121.
USGS. (2023). Landsat 8–9 data users handbook. United States Geological Survey.
Wibowo, A., Nugroho, B., & Setiawan, Y. (2023). Analisis Perubahan Kondisi Vegetasi Menggunakan NDVI Berbasis Citra Sentinel-2 Pada Kawasan Hutan Tropis Indonesia. Jurnal Sylva Lestari, 11(2), 145–157.
Zhu, Z., & Woodcock, C. E. (2018). Continuous Change Detection and Classification of Land Cover Using All Available Landsat Data. Remote Sensing of Environment, 144, 152–171.
Unduhan
Diterbitkan
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2025 Iman Darmatama, Zhaki Restu Pratama, Kemal Alfarid Akbar
Artikel ini berlisensi Creative Commons Attribution-NonCommercial 4.0 International License.