Spatiotemporal Assessment of Landslide-Induced Vegetation Dynamics Using Landsat Satellite Imagery (NDVI), Mount Rinjani, Indonesia (2018-2026) — Oak Academic Publishing
Research ArticleOpen AccessGoogle Scholar indexed
Spatiotemporal Assessment of Landslide-Induced Vegetation Dynamics Using Landsat Satellite Imagery (NDVI), Mount Rinjani, Indonesia (2018-2026)
Natural Resources and Environmental Engineering Study Program (Postgraduate), Department of Biosystem Engineering, Faculty of Agro-Industrial and Biosystems Technology, Universitas Brawijaya, Malang, Indonesia
,
Faculty of Agriculture and Environmental Sciences, University of The Gambia, Faraba, Gambia
,
Faculty of Agriculture and Environmental Sciences, University of The Gambia, Faraba, Gambia
1 Natural Resources and Environmental Engineering Study Program (Postgraduate), Department of Biosystem Engineering, Faculty of Agro-Industrial and Biosystems Technology, Universitas Brawijaya, Malang, Indonesia
2 Faculty of Agriculture and Environmental Sciences, University of The Gambia, Faraba, Gambia
3 Faculty of Agriculture and Environmental Sciences, University of The Gambia, Faraba, Gambia
Landslides are major natural hazards in mountainous regions, frequently triggered by earthquakes and causing significant vegetation loss and long-term ecological degradation. This study evaluates the impact of the 2018 earthquake-triggered landslides on vegetation dynamics in Mount Rinjani National Park (MRNP), Indonesia, using multi-temporal Landsat 8 and 9 Normalized Difference Vegetation Index (NDVI) data from April 2018 to February 2026. NDVI values were extracted from two landslide-affected sites, the Central Rinjani site and the East Rinjani site, to analyze vegetation degradation and recovery across growing and non-growing seasons. A total of 341 statistically significant correlations were identified before multiple-comparison correction, with 281 retained after Benjamini-Hochberg false discovery rate adjustment (q - 1 growing season; +0.0036 NDVI·yr - 1 non-growing season), while the East Rinjani site showed higher growing-season NDVI (mean = 0.592 vs. 0.540), likely due to more favourable local moisture conditions. Pre-disturbance NDVI was positively associated with recovery trajectories, indicating its value as a predictor of post-disturbance regeneration. However, NDVI values remained below pre-disturbance levels by February 2026, suggesting incomplete ecological recovery. These findings highlight the effectiveness of Landsat NDVI for monitoring post-landslide vegetation dynamics and underscore the need for continued long-term observation.
Ambika, K., Alzaben, N., Alghamdi, A.G. and Venkatraman, S. (2025) Integrated Geotechnical and Remote Sensing-Based Monitoring of Unstable Slopes for Landslide Early Warning Using IoT and Sensor Networks. Journal of South American Earth Sciences , 164, Article 105666. https://doi.org/10.1016/j.jsames.2025.105666
Shrestha, M., Sharma, S. and Pradhan Shrestha, R. (2025) Landslides in the Himalayas: A Comprehensive Review of Hazards, Impacts, and Adaptive Strategies. Rural and Regional Development , 3, 10002-10002. https://doi.org/10.70322/rrd.2025.10002
Tynchenko, Y., Kukartsev, V., Tynchenko, V., Kukartseva, O., Panfilova, T., Gladkov, A., et al . (2024) Landslide Assessment Classification Using Deep Neural Networks Based on Climate and Geospatial Data. Sustainability , 16, Article 7063. https://doi.org/10.3390/su16167063
Cui, P., Guo, C., Zhou, J., Hao, M. and Xu, F. (2014) The Mechanisms behind Shallow Failures in Slopes Comprised of Landslide Deposits. Engineering Geology , 180, 34-44. https://doi.org/10.1016/j.enggeo.2014.04.009
Chaudhary, S., Wang, Y., Dixit, A.M., Khanal, N.R., Xu, P., Fu, B., et al . (2019) Spatiotemporal Degradation of Abandoned Farmland and Associated Eco-Environmental Risks in the High Mountains of the Nepalese Himalayas. Land , 9, Article 1. https://doi.org/10.3390/land9010001
Alcántara-Ayala, I. and Sassa, K. (2023) Landslide Risk Management: From Hazard to Disaster Risk Reduction. Landslides , 20, 2031-2037. https://doi.org/10.1007/s10346-023-02140-5
Gong, C., Ni, D., Liu, Y., Li, Y., Huang, Q., Tian, Y., et al . (2024) Herbaceous Vegetation in Slope Stabilization: A Comparative Review of Mechanisms, Advantages, and Practical Applications. Sustainability , 16, Article 7620. https://doi.org/10.3390/su16177620
Yakubu, O. (2017) Addressing Environmental Health Problems in Ogoniland through Implementation of United Nations Environment Program Recommendations: Environmental Management Strategies. Environments , 4, Article 28. https://doi.org/10.3390/environments4020028
Fickert, T. (2020) To Plant or Not to Plant, That Is the Question: Reforestation Vs. Natural Regeneration of Hurricane-Disturbed Mangrove Forests in Guanaja (Honduras). Forests , 11, Article 1068. https://doi.org/10.3390/f11101068
Nava, L., Mondini, A., Bhuyan, K., Fang, C., Monserrat, O., Novellino, A. and Catani, F. (2024) Sentinel-1 SAR-Based Globally Distributed Landslide Detection by Deep Neural Networks. Artificial Intelligence and Robotics. https://doi.org/10.31223/X59D6M
Qodri, M.F., Noviardi, N., Rizqi, A.H.F. and Mase, L.Z. (2021) Numerical Modelling Based on Digital Elevation Model (DEM) Analysis of Debris Flow at Rinjani Volcano, West Nusa Tenggara, Indonesia. Journal of the Civil Engineering Forum , 7, Article 279. https://doi.org/10.22146/jcef.63417
Hadmoko, D.S., Wibowo, S.B., Sianipar, D.S.J., Daryono, D., Fathoni, M.N., Pratiwi, R.S., et al . (2024) Co-Seismic Deformation and Related Hazards Associated with the 2022 Mw 5.6 Cianjur Earthquake in West Java, Indonesia: Insights from Combined Seismological Analysis, Dinsar, and Geomorphological Investigations. Geoenvironmental Disasters , 11, Article No. 15. https://doi.org/10.1186/s40677-024-00277-6
Basuki, T.M., Nugroho, H.Y.S.H., Indrajaya, Y., Pramono, I.B., Nugroho, N.P., Supangat, A.B., et al . (2022) Improvement of Integrated Watershed Management in Indonesia for Mitigation and Adaptation to Climate Change: A Review. Sustainability , 14, Article 9997. https://doi.org/10.3390/su14169997
Nugroho, H.Y.S.H., Nurfatriani, F., Indrajaya, Y., Yuwati, T.W., Ekawati, S., Salminah, M., et al . (2022) Mainstreaming Ecosystem Services from Indonesia’s Remaining Forests. Sustainability , 14, Article 12124. https://doi.org/10.3390/su141912124
Rose, S., Pradeep, G.S. and Vijith, H. (2026) An Investigation of Terrain Recovery by Analyzing the Puthumala Landslide-Impacted Region in Kerala, India, Utilizing Both Pre and Post Disaster NDVI and Land Surface Temperature Data. Discover Hazards , 2, Article No. 10. https://doi.org/10.1007/s44475-026-00016-5
Im, J., Park, H. and Takeuchi, W. (2019) Advances in Remote Sensing-Based Disaster Monitoring and Assessment. Remote Sensing , 11, Article 2181. https://doi.org/10.3390/rs11182181
Reiners, P., Sobrino, J. and Kuenzer, C. (2023) Satellite-Derived Land Surface Temperature Dynamics in the Context of Global Change—A Review. Remote Sensing , 15, Article 1857. https://doi.org/10.3390/rs15071857
Hemati, M., Hasanlou, M., Mahdianpari, M. and Mohammadimanesh, F. (2021) A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth. Remote Sensing , 13, Article 2869. https://doi.org/10.3390/rs13152869
Gu, Z. and Zeng, M. (2023) The Use of Artificial Intelligence and Satellite Remote Sensing in Land Cover Change Detection: Review and Perspectives. Sustainability , 16, Article 274. https://doi.org/10.3390/su16010274
Robinson, N., Allred, B., Jones, M., Moreno, A., Kimball, J., Naugle, D., et al . (2017) A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States. Remote Sensing , 9, Article 863. https://doi.org/10.3390/rs9080863
Huang, S., Tang, L., Hupy, J.P., Wang, Y. and Shao, G. (2020) A Commentary Review on the Use of Normalized Difference Vegetation Index (NDVI) in the Era of Popular Remote Sensing. Journal of Forestry Research , 32, 1-6. https://doi.org/10.1007/s11676-020-01155-1
Bento, V.A., Gouveia, C.M., DaCamara, C.C., Libonati, R. and Trigo, I.F. (2020) The Roles of NDVI and Land Surface Temperature When Using the Vegetation Health Index over Dry Regions. Global and Planetary Change , 190, Article 103198. https://doi.org/10.1016/j.gloplacha.2020.103198
João, T., João, G., Bruno, M. and João, H. (2018) Indicator-Based Assessment of Post-Fire Recovery Dynamics Using Satellite NDVI Time-Series. Ecological Indicators , 89, 199-212. https://doi.org/10.1016/j.ecolind.2018.02.008
Furusawa, T., Koera, T., Siburian, R., Wicaksono, A., Matsudaira, K. and Ishioka, Y. (2023) Time-Series Analysis of Satellite Imagery for Detecting Vegetation Cover Changes in Indonesia. Scientific Reports , 13, Article No. 8437. https://doi.org/10.1038/s41598-023-35330-1
Hartoyo, A.P.P., Pamoengkas, P., Mudzaky, R.H., Khairunnisa, S., Ramadhi, A., Munawir, A., et al . (2022) Estimation of Vegetation Cover Changes Using Normalized Difference Vegetation Index (NDVI) in Mount Halimun Salak National Park, Indonesia. IOP Conference Series : Earth and Environmental Science , 1109, Article 012068. https://doi.org/10.1088/1755-1315/1109/1/012068
Khairunnisa, S., Pamoengkas, P. and Hartoyo, A.P.P. (2024) Analysis of NDVI and Plant Vegetation Diversity in the Traditional Zone, Mount Halimun Salak National Park, Bogor. Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan ( Journal of Natural Resources and Environmental Management ), 14, 109-118. https://doi.org/10.29244/jpsl.14.1.109-118
Lusiana, N., Adliya, G.E., Devianto, L.A. and Husin, N.A. (2026) Rapid Post-Landslide Vegetation Regrowth Detected by Multi-Temporal Satellite Imagery in the Southern Part of Mt. Rinjani National Park, Lombok, Indonesia. Natural Hazards , 122, Article No. 191. https://doi.org/10.1007/s11069-025-07964-z
Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., et al . (2013) High-Resolution Global Maps of 21st-Century Forest Cover Change. Science , 342, 850-853. https://doi.org/10.1126/science.1244693
Fick, S.E. and Hijmans, R.J. (2017) WorldClim 2: New 1‐Km Spatial Resolution Climate Surfaces for Global Land Areas. In ternational Journal of Climatology , 37, 4302-4315. https://doi.org/10.1002/joc.5086
Mar’atusholihah, E.R., Muntasib, E.K.S.H. and Rushayati, S.B. (2021) Tourism Hazard Mitigation in Mount Rinjani National Park, West Nusa Tenggara. Social Science , Humanities and Sustainability Research , 2, p5. https://doi.org/10.22158/sshsr.v2n2p5
Zhao, B., Liao, H. and Su, L. (2021) Landslides Triggered by the 2018 Lombok Earthquake Sequence, Indonesia. CATENA , 207, Article 105676. https://doi.org/10.1016/j.catena.2021.105676
Ang, M., Zubaidah, T., Muhajirah, and Bagus Oka Agastya, I. (2024) Evaluation of Geohazard Mitigation at Mount Rinjani Post-2018 Earthquake. IOP Conference Series : Earth and Environmental Science , 1424, Article 012032. https://doi.org/10.1088/1755-1315/1424/1/012032
Momene Tuwa, B., Fossi, D.H., Nzeugang Nzeukou, A., Ganno, S. and Tsozue, D. (2025) Integrated Analysis of Landslide Susceptibility: Geotechnical Insights, Frequency Ratio Method, and Hazard Mitigation Strategies in a Volcanic Terrain. Arabian Journal of Geosciences , 18, Article No. 76. https://doi.org/10.1007/s12517-025-12221-5
Zhang, J., Zhang, Y., Dannenberg, M.P., Guo, Q., Atkins, J.W., Li, W., et al. (2025) Journal of Hydrology, 651, Article 132595. https://doi.org/10.1016/j.jhydrol.2024.132595
Jie, D., Xiang, Z., Wang, X., Zheng, P., Avtar, R., Xinyu, C., et al . (2024) Post-Seismic Topographic Shifts and Delayed Vegetation Recovery in the Epicentral Area of the 2018 Mw 6.6 Hokkaido Eastern Iburi Earthquake. Progress in Physical Geography : Earth and Environment , 48, 595-614. https://doi.org/10.1177/03091333241269201
Jin, C., Yu, K. and Zhang, K. (2021) Evaluation of Modis-Based Vegetation Restoration after the 2008 Wenchuan Earthquake. E3S Web of Conferences , 308, Article 02005. https://doi.org/10.1051/e3sconf/202130802005
Zhong, C., Li, C., Gao, P. and Li, H. (2021) Discovering Vegetation Recovery and Landslide Activities in the Wenchuan Earthquake Area with Landsat Imagery. Sensors , 21, Article 5243. https://doi.org/10.3390/s21155243
Yunus, A.P., Fan, X., Tang, X., Jie, D., Xu, Q. and Huang, R. (2020) Decadal Vegetation Succession from MODIS Reveals the Spatio-Temporal Evolution of Post-Seismic Landsliding after the 2008 Wenchuan Earthquake. Remote Sensing of Environment , 236, Article 111476. https://doi.org/10.1016/j.rse.2019.111476
Lai, R., Oguchi, T. and Zhong, C. (2022) Evaluating Spatiotemporal Patterns of Post-Eruption Vegetation Recovery at Unzen Volcano, Japan, from Landsat Time Series. Remote Sensing , 14, Article 5419. https://doi.org/10.3390/rs14215419
Saito, H., Uchiyama, S. and Teshirogi, K. (2022) Rapid Vegetation Recovery at Landslide Scars Detected by Multitemporal High-Resolution Satellite Imagery at Aso Volcano, Japan. Geomorphology , 398, Article 107989. https://doi.org/10.1016/j.geomorph.2021.107989
Aman, M.A., Chu, H. and Yunus, A.P. (2024) Exploration of Multi-Decadal Landslide Frequency and Vegetation Recovery Conditions Using Remote-Sensing Big Data. Earth Systems and Environment , 9, 197-213. https://doi.org/10.1007/s41748-024-00432-x
Godwin, P., Tian, S., Duvert, C., Wurm, P., Riwu Kaho, N. and Edwards, A. (2024) Detecting Groundwater Dependence and Woody Vegetation Restoration with NDVI and Moisture Trend Analyses in an Indonesian Karst Savanna. Frontiers in Remote Sensing , 5, Article ID: 1280712. https://doi.org/10.3389/frsen.2024.1280712
Eastman, J., Sangermano, F., Machado, E., Rogan, J. and Anyamba, A. (2013) Global Trends in Seasonality of Normalized Difference Vegetation Index (NDVI), 1982-2011. Remote Sensing , 5, 4799-4818. https://doi.org/10.3390/rs5104799
Galford, G.L., Mustard, J.F., Melillo, J., Gendrin, A., Cerri, C.C. and Cerri, C.E.P. (2008) Wavelet Analysis of MODIS Time Series to Detect Expansion and Intensification of Row-Crop Agriculture in Brazil. Remote Sensing of Environment , 112, 576-587. https://doi.org/10.1016/j.rse.2007.05.017
Pinheiro, C.D.A., Martins, B., Nunes, A., Bento-Gonçalves, A. and Laranjeira, M. (2025) Driving Factors of Post-Fire Vegetation Regrowth in Mediterranean Forest. Land , 14, Article 448. https://doi.org/10.3390/land14030448