Land Use Mapping Using Sentinel-2 Imagery and Volcanic Hazard Zonation for Sustainable Disaster Risk Reduction in the Mount Bromo Area, Probolinggo Regency, Indonesia
DOI:
10.29303/jppipa.v12i4.14874Published:
2026-04-25Downloads
Abstract
This study examines the spatial relationship between land use/land cover (LULC), volcanic hazard zones, and soil conditions in the Mount Bromo area of Probolinggo Regency, East Java, Indonesia. It aims to identify dominant LULC classes, quantify their overlap with volcanic hazard zones, and provide a spatial basis for risk-sensitive land-use planning. Sentinel-2 imagery was classified into four classes: vegetation, open land, agricultural land, and built-up area, and the results were evaluated using a confusion matrix. The classification achieved an overall accuracy of 81.97% and a kappa coefficient of 0.82, indicating reliable performance for regional-scale analysis. Agricultural land was the dominant class, covering 121,477.01 ha or 71.62% of the study area. Volcanic hazard zonation shows that 5,439.86 ha or 3.21% of Probolinggo Regency falls within Mount Bromo’s low-, moderate-, and high-hazard zones, including 941.66 ha or 0.56% in the high-hazard zone. Overlay analysis revealed that 212.39 ha of agricultural land and 16.33 ha of built-up area are located in the high-hazard zone, while 389.45 ha of agricultural land and 9.34 ha of built-up area remain in the moderate-hazard zone. Hazardous zones also spatially coincide with Mollic Andosols, indicating that volcanic risk overlaps with productive soils. These findings show that productive land and settlement-related land use are still not fully aligned with volcanic hazard conditions, highlighting the need for risk-sensitive spatial planning and adaptive land management.
Keywords:
Land use/land cover Mount Bromo Risk-sensitive spatial planning Sentinel-2 imagery Volcanic hazard zonationReferences
Abdullah, U. H., Salima, R., Mulyanti, Mukhlis, & Sufardi. (2024). Soil Quality Index Analysis of Pine Forest Land Use Types on Dryland in Aceh Besar Regency. Jurnal Penelitian Pendidikan IPA, 10(6), 2971–2977. https://doi.org/10.29303/jppipa.v10i6.7228
Anggana, A. F., Savitri, E., Cahyono, S. A., Adi, R. N., Putra, P. B., N. R. P, M., Zakaria, R., & Afandi, M. (2024). Land Vulnerability Analysis for Determining Land Rehabilitation Directions for Soil Conservation in Conservation District: Case Study of Tamansari District, Boyolali Regency. Jurnal Penelitian Pendidikan IPA, 10(11), 9780–9790. https://doi.org/10.29303/jppipa.v10i11.9519
Arfa, A., & Minaei, M. (2024). Utilizing multitemporal indices and spectral bands of Sentinel-2 to enhance land use and land cover classification with random forest and support vector machine. Advances in Space Research, 74(11), 5580–5590. https://doi.org/10.1016/j.asr.2024.08.062
Bachri, S., Shrestha, R. P., Sumarmi, Irawan, L. Y., Masruroh, H., Prastiwi, M. R. H., Billah, E. N., Putri, N. R. C., Hakiki, A. R. R., & Hidiyah, T. M. (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
Bonadonna, C., Frischknecht, C., Menoni, S., Romerio, F., Gregg, C. E., Rosi, M., Biass, S., Asgary, A., Pistolesi, M., Guobadia, D., Gattuso, A., Ricciardi, A., & Cristiani, C. (2021). Integrating hazard, exposure, vulnerability and resilience for risk and emergency management in a volcanic context: The ADVISE model. Journal of Applied Volcanology, 10(1), 7. https://doi.org/10.1186/s13617-021-00108-5
Budiman, S. A., Istiqomah, S., Purnamasari, I., Suud, H. M., Kusbianto, D. E., & Mechram, S. (2025). Determination of sampling points in rice fields and rainfed rice fields based on characteristics of land resources using GIS and K-mean cluster. IOP Conference Series: Earth and Environmental Science, 1477(1), 012010. https://doi.org/10.1088/1755-1315/1477/1/012010
Chandra, Y. I. I., Maryanto, S., & Susilo, A. (2025). Monitoring Mount Semeru’s 2021 Eruption using NDVI and LST from Sentinel Satellite. Jurnal Penelitian Pendidikan IPA, 11(4), 1203–1209. https://doi.org/10.29303/jppipa.v11i4.10605
Chaves, M. E. D., Soares, A. R., Mataveli, G. A. V., Sánchez, A. H., & Sanches, I. D. (2023). A Semi-Automated Workflow for LULC Mapping via Sentinel-2 Data Cubes and Spectral Indices. Automation, 4(1), 94–109. https://doi.org/10.3390/automation4010007
Chedid, E., Avia, K., Dumas, V., Ley, L., Reibel, N., Butterlin, G., Soma, M., Lopez-Lozano, R., Baret, F., Merdinoglu, D., & Duchêne, É. (2023). LiDAR Is Effective in Characterizing Vine Growth and Detecting Associated Genetic Loci. Plant Phenomics, 5, 0116. https://doi.org/10.34133/plantphenomics.0116
Chen, S., Arrouays, D., Leatitia Mulder, V., Poggio, L., Minasny, B., Roudier, P., Libohova, Z., Lagacherie, P., Shi, Z., Hannam, J., Meersmans, J., Richer-de-Forges, A. C., & Walter, C. (2022). Digital mapping of GlobalSoilMap soil properties at a broad scale: A review. Geoderma, 409, 115567. https://doi.org/10.1016/j.geoderma.2021.115567
Faoziyah, U., Rosyaridho, M. F., & Panggabean, R. (2024). Unearthing Agricultural Land Use Dynamics in Indonesia: Between Food Security and Policy Interventions. Land, 13(12), 2030. https://doi.org/10.3390/land13122030
Ghayour, L., Neshat, A., Paryani, S., Shahabi, H., Shirzadi, A., Chen, W., Al-Ansari, N., Geertsema, M., Pourmehdi Amiri, M., Gholamnia, M., Dou, J., & Ahmad, A. (2021). Performance Evaluation of Sentinel-2 and Landsat 8 OLI Data for Land Cover/Use Classification Using a Comparison between Machine Learning Algorithms. Remote Sensing, 13(7), 1349. https://doi.org/10.3390/rs13071349
Gholami, F., Li, Y., Zhang, J., & Nemati, A. (2023). Quantitative Assessment of Future Land Use Changes’ Impact on Flood Risk Components: Integration of Remote Sensing, Machine Learning, and Hydraulic Modeling. https://doi.org/10.21203/rs.3.rs-3632802/v1
Ibrahim, M., Huo, A., Ullah, W., Ullah, S., Ahmad, A., & Zhong, F. (2024). Flood vulnerability assessment in the flood prone area of Khyber Pakhtunkhwa, Pakistan. Frontiers in Environmental Science, 12, 1303976. https://doi.org/10.3389/fenvs.2024.1303976
Indarto, I., & Hakim, F. L. (2021). Tracking Land Use Land Cover changes from 2000 to 2018 in a local area of East Java Province, Indonesia. Bulletin of Geography Socio-Economic Series, 52(52), 7–24. https://doi.org/10.2478/bog-2021-0010
Junianto, M., Sugianto, S., & Basri, H. (2023). Analysis of Changes in Mangrove Land Cover in West Langsa District, Langsa. Jurnal Penelitian Pendidikan IPA, 9(3), 1155–1162. https://doi.org/10.29303/jppipa.v9i3.2963
Kumari, A., & Karthikeyan, S. (2023). Sentinel-2 Data for Land Use/Land Cover Mapping: A Meta-analysis and Review. SN Computer Science, 4(6), 815. https://doi.org/10.1007/s42979-023-02214-0
Leenaars, J. G. B., Elias, E., Wösten, J. H. M., Ruiperez-González, M., & Kempen, B. (2020). Mapping the major soil-landscape resources of the Ethiopian Highlands using random forest. Geoderma, 361, 114067. https://doi.org/10.1016/j.geoderma.2019.114067
Li, Y., Gao, J., Yin, J., Liu, L., Zhang, C., & Wu, S. (2024). Flood Risk Assessment of Areas under Urbanization in Chongqing, China, by Integrating Multi-Models. Remote Sensing, 16(2), 219. https://doi.org/10.3390/rs16020219
Lindsay, J. M., Charlton, D., Clive, M. A. T., Bertin, D., Ogburn, S., Wright, H., Ewert, J., Calder, E. S., & Steinke, B. (2023). The diversity of volcanic hazard maps around the world: Insights from map makers. Journal of Applied Volcanology, 12(1), 8. https://doi.org/10.1186/s13617-023-00134-5
Mandala, M., Indarto, I., Mas’udi, Ach. F., & Saputra, A. A. (2023). Land Use and Land Cover (LULC) Change in Eastern Areas of East Java From 1972 To 2021: Learning From Landsat Image. Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering), 12(4), 1022. https://doi.org/10.23960/jtep-l.v12i4.1022-1035
Mappatoba, C. A., Rachman, I., Malik, A., Golar, Massiri, S. Dg., & Alam, A. S. (2025). Spatial Dynamics of Land Cover Change in the Ngata Toro Customary Forest, Toro Village, Kulawi District, Sigi Regency, from 2021 to 2025. Jurnal Penelitian Pendidikan IPA, 11(12), 11–19. https://doi.org/10.29303/jppipa.v11i12.12698
Marin, R. J., Marín-Sánchez, J. C., Mira, J. E., García, E. F., Zhao, B., & Zambrano, J. (2024). Landslide Hazard and Rainfall Threshold Assessment: Incorporating Shallow and Deep-Seated Failure Mechanisms with Physics-Based Models. Geosciences, 14(10), 280. https://doi.org/10.3390/geosciences14100280
Masiero, M., Bottaro, G., Righetti, C., Nikolaidis, N. P., Lilli, M. A., & Pettenella, D. (2024). Riparian Forests as Nature-Based Solutions within the Mediterranean Context: A Biophysical and Economic Assessment for the Koiliaris River Watershed (Crete, Greece). Forests, 15(5), 760. https://doi.org/10.3390/f15050760
Nasiri, V., Deljouei, A., Moradi, F., Sadeghi, S. M. M., & Borz, S. A. (2022). Land Use and Land Cover Mapping Using Sentinel-2, Landsat-8 Satellite Images, and Google Earth Engine: A Comparison of Two Composition Methods. Remote Sensing, 14(9), 1977. https://doi.org/10.3390/rs14091977
Nurhasanah, Hamzah, A. H. P., & Harijati, S. (2023). Citra Landsat 8 on Environmental Spatial Analysis for Determining the Zone of Mangrove Distribution in Langkat District. Jurnal Penelitian Pendidikan IPA, 9(11), 10028–10032. https://doi.org/10.29303/jppipa.v9i11.3950
Orynbaikyzy, A., Santoso, I., Rösch, M., Martinis, S., Ismanto, R. D., Vetrita, Y., Khomarudin, M. R., Strunz, G., & Plank, S. (2025). Land surface change detection after major volcanic eruptions in Indonesia using Machine learning and Spatial-Temporal transferability. International Journal of Applied Earth Observation and Geoinformation, 145, 104965. https://doi.org/10.1016/j.jag.2025.104965
Praveen, D., & Kunnampalli, J. (2024). Evaluating the impacts of anticipated sea level rise, climate change and land use land cover scenarios on the rice crop in Alappuzha, Kerala and strategies to build climate responsive agriculture. International Journal of Disaster Resilience in the Built Environment, 15(4), 755–775. https://doi.org/10.1108/IJDRBE-05-2023-0066
Purwanto, A., & Paiman, P. (2023). Flood Risk Spatial Modeling Based on Geographical Information Systems and Remote Sensing in the Pemangkat Regensi. Jurnal Penelitian Pendidikan IPA, 9(11), 9554–9563. https://doi.org/10.29303/jppipa.v9i11.5264
Reyes-Hardy, M.-P., Aguilera Barraza, F., Sepúlveda Birke, J. P., Esquivel Cáceres, A., & Inostroza Pizarro, M. (2021). GIS-based volcanic hazards, vulnerability and risks assessment of the Guallatiri Volcano, Arica y Parinacota Region, Chile. Journal of South American Earth Sciences, 109, 103262. https://doi.org/10.1016/j.jsames.2021.103262
Rifai, M., & Harintaka. (2024). Integration of Cloud Score+ with Sentinel-2 Harmonized for land use and land cover classification using machine learning algorithms. IOP Conference Series: Earth and Environmental Science, 1418(1), 012039. https://doi.org/10.1088/1755-1315/1418/1/012039
Rumora, L., Miler, M., & Medak, D. (2020). Impact of Various Atmospheric Corrections on Sentinel-2 Land Cover Classification Accuracy Using Machine Learning Classifiers. ISPRS International Journal of Geo-Information, 9(4), 277. https://doi.org/10.3390/ijgi9040277
Saputra, D. D., Sari, R. R., Hairiah, K., Widianto, Suprayogo, D., & Van Noordwijk, M. (2022). Recovery after volcanic ash deposition: Vegetation effects on soil organic carbon, soil structure and infiltration rates. Plant and Soil, 474(1–2), 163–179. https://doi.org/10.1007/s11104-022-05322-7
Sari, R. R., Priyadarshini, R., Rozendaal, D. M. A., Saputra, D. D., Hairiah, K., & Van Noordwijk, M. (2023). Tree diversity and social–ecological resilience of agroforestry after volcanic ash deposition in Indonesia. Sustainability Science, 18(6), 2735–2753. https://doi.org/10.1007/s11625-023-01400-6
Seeger, K., Peffeköver, A., Minderhoud, P. S. J., Vogel, A., Brückner, H., Kraas, F., Oo, N. W., & Brill, D. (2024). Evaluating flood hazards in data-sparse coastal lowlands: Highlighting the Ayeyarwady Delta (Myanmar). Environmental Research Letters, 19(8), 084007. https://doi.org/10.1088/1748-9326/ad5b07
Sisay, M. G., Tsegaye, E. A., Tolossa, A. R., Nyssen, J., Frankl, A., Van Ranst, E., & Dondeyne, S. (2024). Soil-Forming Factors of High-Elevation Mountains along the East African Rift Valley: The Case of the Mount Guna Volcano, Ethiopia. Soil Systems, 8(2), 38. https://doi.org/10.3390/soilsystems8020038
Suprayogo, D., Van Noordwijk, M., Hairiah, K., Meilasari, N., Rabbani, A. L., Ishaq, R. M., & Widianto, W. (2020). Infiltration-Friendly Agroforestry Land Uses on Volcanic Slopes in the Rejoso Watershed, East Java, Indonesia. Land, 9(8), 240. https://doi.org/10.3390/land9080240
Thakur, T. K., Swamy, S. L., Dutta, J., Thakur, A., Mishra, A., Sarangi, P. K., Kumar, A., Almutairi, B. O., & Kumar, R. (2024). Assessment of land use dynamics and vulnerability to land degradation in coal-mined landscapes of central India: Implications for ecorestoration strategies. Frontiers in Environmental Science, 12, 1419041. https://doi.org/10.3389/fenvs.2024.1419041
Topuz, M., & Deniz, M. (2023). Application of GIS and AHP for land use suitability analysis: Case of Demirci district (Turkey). Humanities and Social Sciences Communications, 10(1), 115. https://doi.org/10.1057/s41599-023-01609-x
Toulier, A., Baud, B., De Montety, V., Lachassagne, P., Leonardi, V., Pistre, S., Dautria, J.-M., Hendrayana, H., Miftakhul Fajar, M. H., Satrya Muhammad, A., Beon, O., & Jourde, H. (2019). Multidisciplinary study with quantitative analysis of isotopic data for the assessment of recharge and functioning of volcanic aquifers: Case of Bromo-Tengger volcano, Indonesia. Journal of Hydrology: Regional Studies, 26, 100634. https://doi.org/10.1016/j.ejrh.2019.100634
Widjajanto, D., Zainuddin, R., Rois, Rahman, A., Khaliq, Moh. A., Hasanah, U., Gailea, R., & Fera. (2025). Dynamics of Soil Organic Carbon at Different Elevations in Cocoa Land-Use Systems. Jurnal Penelitian Pendidikan IPA, 11(7), 561–569. https://doi.org/10.29303/jppipa.v11i7.11999
Yuli Handoko, E., Fahriza, A., & Muryono, M. (2024). Integrating Remote Sensing and GIS for Precision Agriculture: Leveraging Google Earth Engine for Enhanced Agricultural Management. IOP Conference Series: Earth and Environmental Science, 1418(1), 012054. https://doi.org/10.1088/1755-1315/1418/1/012054
Zairina, A., Soemarno, S., Rachmansyah, A., & Yanuwiadi, B. (2024). Geophysical, geotechnical, and vegetation characteristics in landslide areas in Pujon and Ngantang, Malang Regency, East Java. Journal of Degraded and Mining Lands Management, 11(2), 5211–5223. https://doi.org/10.15243/jdmlm.2024.112.5211
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