LAND USE SIMULATION TO FOSTER ENVIRONMENTAL SUSTAINABILITY OF THE RANU PANE VOLCANIC LAKE, INDONESIA
DOI:
https://doi.org/10.21837/pm.v24i40.1958Keywords:
Land Change Modeler, Land Use Change, Ranu Pane Volcanic Lake, Semeru VolcanoAbstract
Sedimentation in the Ranu Pane Volcanic Lake (RPVL) has increased due to land use change (LUC) in the surrounding area and the considerable outflow of materials from the Semeru volcanic eruption. The continued sedimentation will have negative consequences for humans and the sustainability of the RPVL. This research was aimed at building a LUC simulation model for 2024-2036 using a land change modeler (LCM) with the Logistic Regression/Markov Chain algorithm and a built-up land scenario based on historical land use (LU) data to investigate future sedimentation. The secondary data were mosaics from Planet Labs® Norway's International Climate and Forest Initiative (NICFI) imagery, roads, rivers, slopes, elevation, rainfall, and soil types. The primary data collected through fieldwork for validation of the LU were processed using remote sensing and the Geographic Information System (GIS). The simulation model for 2024-2036 was built using the LU data for 2016, 2020, and 2024. The LCM model detected that there would be a decrease in forest area but an increase in built-up land and agriculture in the study area between 2024–2036. The findings indicate that the increased land area and agriculture around Mount Semeru will lead to further sedimentation. The study findings can help planners understand LU patterns and their impacts, which can be useful in designing sustainable lake development strategies and management plans for the area.
Downloads
References
Bachri, S., Shrestha, R., Sumarmi, S., Irawan, L., Masruroh, H., Regina, M., Billah, E., Putri, N., Hakiki, A., & Hidiyah, T. (2024). Land Use Change Simulation Model Using a Land Change Modeler in Anticipation of the Impact of the Semeru Volcano Eruption Disaster in Indonesia. Environmental Challenges, 14, 100862. https://doi.org/10.1016/j.envc.2024.100862
Badshah, M. T., Hussain, K., Rehman, A. U., Mehmood, K., Muhammad, B., Wiarta, R., Silamon, R. F., Khan, M. A., & Meng, J. (2024). The role of random forest and Markov chain models in understanding metropolitan urban growth trajectory. Frontiers in Forests and Global Change, 7(March), 1–17. https://doi.org/10.3389/ffgc.2024.1345047
Brown, G., Sanders, S., & Reed, P. (2018). Using public participatory mapping to inform general land use planning and zoning. Landscape and Urban Planning, 177. https://doi.org/10.1016/j.landurbplan.2018.04.011
Cao, F., Dan, L., Ma, Z., & Gao, T. (2021). The impact of land use and land cover change on regional climate over East Asia during 1980–2010 using a coupled model. Theoretical and Applied Climatology, 145(1–2), 549–565. https://doi.org/10.1007/s00704-021-03629-6
Entahabu, H. H., Minale, A. S., & Birhane, E. (2023). Modeling and Predicting Land Use/Land Cover Change Using the Land Change Modeler in the Suluh River Basin, Northern Highlands of Ethiopia. Sustainability (Switzerland), 15(10). https://doi.org/10.3390/su15108202
Faheem, Z., Kazmi, J. H., Shaikh, S., Arshad, S., Noreena, & Mohammed, S. (2024). Random forest-based analysis of land cover/land use LCLU dynamics associated with meteorological droughts in the desert ecosystem of Pakistan. Ecological Indicators, 159, 111670. https://doi.org/https://doi.org/10.1016/j.ecolind.2024.111670
Feizizadeh, B., Omarzadeh, D., Kazemi Garajeh, M., Lakes, T., & Blaschke, T. (2023). Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine. Journal of Environmental Planning and Management, 66(3), 665–697. https://doi.org/10.1080/09640568.2021.2001317
Haider, S., & Rashid, M. (2024). Integrated Assessment of CMIP6 Models and Land Cover Change on Water Resources of the Hunza Basin in the Upper Indus.
Masolele, R. N., Marcos, D., De Sy, V., Abu, I. O., Verbesselt, J., Reiche, J., & Herold, M. (2024). Mapping the diversity of land uses following deforestation across Africa. Scientific Reports, 14(1), 1–16. https://doi.org/10.1038/s41598-024-52138-9
Maulana, M. I., Subagiyo, I., & Nugroho, B. A. (2021). Local Awareness of Agriculture and Livestock Integration in Maintaining the Value of the Ranu Pani Lake Conservation. International Research Journal of Advanced Engineering and Science, 6(1), 227–232. http://irjaes.com/wp-content/uploads/2021/02/IRJAES-V6N1P185Y21.pdf
Motovalibashi Naeini, A., Tabesh, M., & Soltaninia, S. (2024). Modeling the effect of land use change to design a suitable low impact development (LID) system to control surface water pollutants. The Science of the Total Environment, 932, 172756. https://doi.org/10.1016/j.scitotenv.2024.172756
Pontius Jr, R. G., & Millones, M. (2011). Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing, 32(15), 4407–4429. https://doi.org/10.1080/01431161.2011.552923
Pourghasemi, H. R., Kariminejad, N., Gayen, A., & Komac, M. (2020). Statistical functions used for spatial modelling due to assessment of landslide distribution and landscape-interaction factors in Iran. Geoscience Frontiers, 11(4), 1257–1269. https://doi.org/10.1016/j.gsf.2019.11.005
Putri, G. A. W., Nugroho, D. P., & P, B. P. P. (2022). Perancangan Buku Fotografi Petani Ranu Pani Untuk Memberikan Wawasan Visual Kepada Calon Wisatawan. Sainsbertek Jurnal Ilmiah Sains & Teknologi, 3(1), 75–90. https://doi.org/10.33479/sb.v3i1.189
Satir, O., Kemec, S., Yeler, O., Akin, A., Aslantaş, P., & Ersoy, M. (2023). Simulating the impact of natural disasters on urban development in a sample of earthquake. Natural Hazards, 116, 1–17. https://doi.org/10.1007/s11069-023-05838-w
Smith, V., Devane, D., Begley, C. M., Clarke, M., Penelitian, B. M., Surahman, Rachmat, M., Supardi, S., Saputra, R., NURYADI, TUTUT DEWI ASTUTI, ENDANG SRI UTAMI, MARTINUS BUDIANTARA, Sastroasmoro, S., Çelik, A., Yaman, H., Turan, S., Kara, A., Kara, F., … Hastono, S. P. (2017). No 主観的健康感を中心とした在宅高齢者における 健康関連指標に関する共分散構造分析Title. Journal of Materials Processing Technology, 1(1), 1–8. http://dx.doi.org/10.1016/j.cirp.2016.06.001%0Ahttp://dx.doi.org/10.1016/j.powtec.2016.12.055%0Ahttps://doi.org/10.1016/j.ijfatigue.2019.02.006%0Ahttps://doi.org/10.1016/j.matlet.2019.04.024%0Ahttps://doi.org/10.1016/j.matlet.2019.127252%0Ahttp://dx.doi.o
Suharto, B., Anugroho, F., & Arifin, B. (2023). Analisis Tingkat Bahaya Erosi Pada Lahan Pertanian di Desa Ranu Pani Taman Nasional Bromo Tengger Semeru. Jurnal Sumberdaya Alam Dan Lingkungan, 10(2), 88–96. https://doi.org/10.21776/ub.jsal.2023.010.02.5
Sujana, F. R., Chaidar, A. N., & Hatmoko, W. (2024). Study on the Impact of Land Use Changes Caused by IKN Development on Sanggai River Flood Discharge. E3S Web of Conferences, 500, 1–8. https://doi.org/10.1051/e3sconf/202450002019
Thouret, J. C., Wavelet, E., Taillandier, M., Tjahjono, B., Jenkins, S. F., Azzaoui, N., & Santoni, O. (2022). Defining population socio-economic characteristics, hazard knowledge and risk perception: The adaptive capacity to persistent volcanic threats from Semeru, Indonesia. International Journal of Disaster Risk Reduction, 77. https://doi.org/10.1016/j.ijdrr.2022.103064
Turner, M., & Gardner, R. (2015). Landscape ecology in theory and practice: Pattern and process, second edition. https://doi.org/10.1007/978-1-4939-2794-4
Viera, A. J., & Garrett, J. M. (2005). Understanding interobserver agreement: the kappa statistic. Family Medicine, 37(5), 360–363.
Wiwoho, B. S., McIntyre, N., & Phinn, S. (2024). Assessing future land-uses under planning scenarios: A case study of The Brantas River Basin, Indonesia. Environmental Challenges, 15, 100873. https://doi.org/https://doi.org/10.1016/j.envc.2024.100873
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 Unported License.
Copyright & Creative Commons Licence
eISSN: 0128-0945 © Year. The Authors. Published for Malaysian Institute of Planners. This is an open-access article under the CC BY-NC-ND license.
The authors hold the copyright without restrictions and also retain publishing rights without restrictions.