OPTIMIZATION OF LAND USE MAPPING USING SENTINEL IMAGERY TO SUPPORT FLOOD DISASTER MITIGATION IN TORUE DISTRICT

Widyastuti Widyastuti, Exsa Putra, Amalia Novarita, Rahmawati Rahmawati

Abstract

To mitigate risk, effective land use planning must consider these socioeconomic factors. Numerous natural disasters will be brought on by improper land modification—the interaction between climate change and land-use change, such as deforestation. Different types of land transformation, such as cultivation and reforestation, are understood in varying ways. This study aims to accurately map land use by utilising GIS and Sentinel-2 data to support disaster mitigation efforts in Torue District. This study adopts a spatial approach and a descriptive quantitative method. Descriptive statistics are employed in this study's data analysis to illustrate the spatial characteristics of the study region, based on satellite image interpretation and GIS data processing. The results obtained eight land use classes. High-quality satellite imagery is required for accurate classification. Similarly, between classes and high intra-class variation can complicate the classification process, requiring advanced techniques to improve accuracy. Land use mapping produced eight classes with a total area of 26,467 ha, achieving an Overall Accuracy of 94.43%.

Keywords

land use; mapping; classification; optimization; Sentinel

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References

‘Audah, S., Nazliyati, Bakruddin, Saputra, E., Wathan, S., Rizky, M. M., & Rizky, M. M. (2019). Visual Analysis of Satellite Landsat Images Multitemporal and GPS as a Geographic Information System for Mapping of Nugmet Plantations in Tapaktuan. IOP Conference Series: Materials Science and Engineering, 506(1), 012037. https://doi.org/10.1088/1757-899X/506/1/012037

Ahlqvist, O. (2009). Geographic Information Systems, Overlay in. In International Encyclopedia of Human Geography (pp. 49–56). Elsevier. https://doi.org/10.1016/B978-0-08-102295-5.10582-7

Assaf, G., & Assaad, R. H. (2024). A Novel Approach for Classifying the Management Priorities of Flooding Events Using Clustering Algorithms and Geospatial Analysis. Construction Research Congress 2024, CRC 2024, 2, 226–236. https://doi.org/10.1061/9780784485279.024

Azadi, H., Barati, A. A., Nazari Nooghabi, S., & Scheffran, J. (2022). Climate-related disasters and agricultural land conversion: towards prevention policies. Climate and Development, 14(9), 814–828. https://doi.org/10.1080/17565529.2021.2008291

Backes, D. J., & Teferle, F. N. (2020). Multiscale Integration of High-Resolution Spaceborne and Drone-Based Imagery for a High-Accuracy Digital Elevation Model Over Tristan da Cunha. Frontiers in Earth Science, 8. https://doi.org/10.3389/feart.2020.00319

Bofjäll, A. S., Hassel, H., & Cedergren, A. (2020). Managing Multiple Risks in Land use Planning – A Literature Review. Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference, 572–579. Singapore: Research Publishing Services. https://doi.org/10.3850/978-981-14-8593-0_5729-cd

Cheng, Y., Zhang, X., & Song, W. (2024). Ecological Risk Assessment of Land Use Change in the Tarim River Basin, Xinjiang, China. Land, 13(4), 561. https://doi.org/10.3390/land13040561

Danoedoro, P., Ananda, I. N., Kartika, C. S. D., Umela, A. F., & Indayani, A. B. (2020). Testing a detailed classification scheme for land-cover/ land-use mapping of typical Indonesian landscapes: case study of Sarolangun, Jambi and Salatiga, Central Java. Indonesian Journal of Geography, 52(3), 327. https://doi.org/10.22146/ijg.50080

Debnath, J., Sahariah, D., Meraj, G., Chand, K., Singh, S. K., Kanga, S., & Kumar, P. (2024). Assessing critical flood-prone districts and optimal shelter zones in the Brahmaputra Valley: Strategies for effective flood risk management. Physics and Chemistry of the Earth, 136. https://doi.org/10.1016/j.pce.2024.103772

Dewi, R. S., Handayani, W., Rudiarto, I., & Artiningsih. (2022). Understanding the Connection between Urbanization and Hydrometeorological Disasters: an Experience from Central Java Province, Indonesia. IOP Conference Series: Earth and Environmental Science, 1039(1), 012015. https://doi.org/10.1088/1755-1315/1039/1/012015

Fikri, A. A., Darmawan, A., Hilmanto, R., Banuwa, I. S., Agustiono, A., & Agustiana, L. (2022). Pemanfaatan platform Google Earth Engine dalam Pemantauan Perubahan Tutupan Lahan di Taman Hutan Raya Wan Abdul Rachman. Journal of Forest Science Avicennia, 5(1), 46–57. https://doi.org/10.22219/avicennia.v5i1.19938

Islami, F. A., Tarigan, S. D., Wahjunie, E. D., & Dasanto, B. D. (2022). Accuracy Assessment of Land Use Change Analysis Using Google Earth in Sadar Watershed Mojokerto Regency. IOP Conference Series: Earth and Environmental Science, 950(1), 012091. https://doi.org/10.1088/1755-1315/950/1/012091

Issa, S., & Sultan, M. (2024). Land use and land cover mapping using Google Earth Engine: A comparative analysis of machine learning algorithms. Seventh International Conference on Engineering Geophysics, Al Ain, UAE, 16–19 October 2023, 147–151. Society of Exploration Geophysicists. https://doi.org/10.1190/iceg2023-034.1

Kapitza, S., Golding, N., & Wintle, B. A. (2022). A fractional land use change model for ecological applications. Environmental Modelling & Software, 147, 105258. https://doi.org/10.1016/j.envsoft.2021.105258

Krishna, A. P., & Mukherjee, A. B. (2022). Satellite and aerial remote sensing in disaster management: An introduction. In Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention (pp. 273–280). Elsevier. https://doi.org/10.1016/B978-0-323-91166-5.00004-5

Lebedeva, E. V, Baldina, E. A., & Medvedev, A. A. (2022). Use Of Multi-Temporal High Resolution Space Images To Analyze The Slope Processes In The Geysernaya River Valley (Kamchatka). Geomorphology, 53(4), 3–16. https://doi.org/10.31857/S0435428122040095

Li, B. V, Jenkins, C. N., & Xu, W. (2022). Strategic protection of landslide vulnerable mountains for biodiversity conservation under land-cover and climate change impacts. Proceedings of the National Academy of Sciences, 119(2). https://doi.org/10.1073/pnas.2113416118

Lindner, C., Degbelo, A., Vassányi, G., Kundert, K., & Schwering, A. (2023). The SmartLandMaps Approach for Participatory Land Rights Mapping. Land, 12(11), 2043. https://doi.org/10.3390/land12112043

Liu, Y., Zheng, M., & Zhou, N. (2021). Analysis on Impact of Land Use Change on Urban Waterlogging Caused by Floods. E3S Web of Conferences, 233, 03036. https://doi.org/10.1051/e3sconf/202123303036

Marino, D., Palmieri, M., Marucci, A., Soraci, M., Barone, A., & Pili, S. (2023). Linking Flood Risk Mitigation and Food Security: An Analysis of Land-Use Change in the Metropolitan Area of Rome. Land, 12(2), 366. https://doi.org/10.3390/land12020366

Maund, K., Maund, M., & Gajendran, T. (2022). Land use planning: An opportunity to avert devastation from bushfires. Environment and Planning B: Urban Analytics and City Science, 49(5), 1371–1388. https://doi.org/10.1177/23998083211064291

Moayedi, H., Jamali, A., Gibril, M. B. A., Kok Foong, L., & Bahiraei, M. (2020). Evaluation of tree-base data mining algorithms in land used/land cover mapping in a semi-arid environment through Landsat 8 OLI image; Shiraz, Iran. Geomatics, Natural Hazards and Risk, 11(1), 724–741. https://doi.org/10.1080/19475705.2020.1745902

Morales, F. F., & de Vries, W. T. (2021). Establishment of Natural Hazards Mapping Criteria Using Analytic Hierarchy Process (AHP). Frontiers in Sustainability, 2. https://doi.org/10.3389/frsus.2021.667105

Narendr, A., Vinay, S., Aithal, B. H., & Das, S. (2022). Multi-dimensional parametric coastal flood risk assessment at a regional scale using GIS. Environment, Development and Sustainability, 24(7), 9569–9597. https://doi.org/10.1007/s10668-021-01839-6

Novarita, A., Rahmawati, R., & Putra, E. (2025). Mapping The Level Of Preparedness Community For Earthquake Disaster Using Spatial Approach In Central Of Sulawesi. GeoEco, 11(1), 27–42. https://doi.org/10.20961/ge.v11i1.93788

Pabi, O., Egyir, S., & Attua, E. M. (2021). Flood hazard response to scenarios of rainfall dynamics and land use and land cover change in an urbanized river basin in Accra, Ghana. City and Environment Interactions, 12, 100075. https://doi.org/10.1016/j.cacint.2021.100075

Pande, C. B., Diwate, P., Orimoloye, I. R., Sidek, L. M., Pratap Mishra, A., Moharir, K. N., … Tolche, A. D. (2024). Impact of land use/land cover changes on evapotranspiration and model accuracy using Google Earth engine and classification and regression tree modeling. Geomatics, Natural Hazards and Risk, 15(1). https://doi.org/10.1080/19475705.2023.2290350

Pande, C. B., Moharir, K. N., & Khadri, S. F. R. (2021). Assessment of land-use and land-cover changes in Pangari watershed area (MS), India, based on the remote sensing and GIS techniques. Applied Water Science, 11(6), 96. https://doi.org/10.1007/s13201-021-01425-1

Pereira, P., Gomes, E., & Rocha, J. (2022). Mapping and Forecasting Land Use. In Mapping and Forecasting Land Use: The Present and Future of Planning. Elsevier. https://doi.org/10.1016/C2020-0-02839-2

Putra, E., Fitriana, T., Nutfa, M., & Teguh, M. (2025). Analysis the mitigation of floods in the junior high school students in Torue District: 21st-century learning skills. IOP Conference Series: Earth and Environmental Science, 1462(1), 012013. https://doi.org/10.1088/1755-1315/1462/1/012013

Putra, P. B., Agus, C., Adi, R. N., Susanti, P. D., & Indrajaya, Y. (2021). Land Use Change in Tropical Watersheds: Will It Support Natural Resources Sustainability? In World Sustainability Series (pp. 63–75). https://doi.org/DOI https://doi.org/10.1007/978-3-030-76624-5_5

Rainey, J. L., Brody, S. D., Galloway, G. E., & Highfield, W. E. (2021). Assessment of the growing threat of urban flooding: a case study of a national survey. Urban Water Journal, 18(5), 375–381. https://doi.org/10.1080/1573062X.2021.1893356

Rizaldi, A., Darmawan, A., Kaskoyo, H., & Setiawan, A. (2022). Pemanfaatan google earth engine untuk pemantauan lahan agroforestri dalam skema perhutanan sosial. Majalah Geografi Indonesia, 37(1), 12. https://doi.org/10.22146/mgi.73923

Rugel, G. M. V., Van Coillie, F., & Ochoa, D. (2021). Mapping and Assessment of Land Use and Land Cover for Different Ecoregions of Ecuador Using Phenology-Based Classification. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 6492–6495. IEEE. https://doi.org/10.1109/IGARSS47720.2021.9554218

Sharma, N., & Chawla, S. (2023). Digital Change Detection Analysis Criteria and Techniques used for Land Use and Land Cover Classification in Agriculture. 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 331–335. IEEE. https://doi.org/10.1109/ICACITE57410.2023.10182604

Szarek-Iwaniuk, P., Dawidowicz, A., & Senetra, A. (2022). Methodology for Precision Land Use Mapping towards Sustainable Urbanized Land Development. International Journal of Environmental Research and Public Health, 19(6), 3633. https://doi.org/10.3390/ijerph19063633

Tarko, A., Tsendbazar, N. E., de Bruin, S., & Bregt, A. K. (2020). Influence of image availability and change processes on consistency of land transformation interpretations. International Journal of Applied Earth Observation and Geoinformation, 86, 102005. https://doi.org/10.1016/j.jag.2019.102005

Tasantab, J. C. (2019). Beyond the plan: How land use control practices influence flood risk in Sekondi-Takoradi. Jàmbá Journal of Disaster Risk Studies, 11(1), 1–9. https://doi.org/10.4102/jamba.v11i1.638

Tehsin, S., Kausar, S., Jameel, A., Humayun, M., & Almofarreh, D. K. (2023). Satellite Image Categorization Using Scalable Deep Learning. Applied Sciences, 13(8), 5108. https://doi.org/10.3390/app13085108

Thepade, S. D., & Bhalerao, A. P. (2023). Machine Learning based Land Use Identification of Aerial Images with Fusion of Thepade SBTC and Triangle Thresholding. 2023 2nd International Conference for Innovation in Technology (INOCON), 1–7. IEEE. https://doi.org/10.1109/INOCON57975.2023.10101262

Vinuja, G., & Devi, N. B. (2023). Remote Sensing Evaluation of Environmental Factors for Disease Prediction by RS-GIS. 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT), 1–5. IEEE. https://doi.org/10.1109/EASCT59475.2023.10392674

Widyastuti, Hartono, & Kurniawan, A. (2025). Application of Geographic Information Systems and Analytical Hierarchy Process for Coastal Land Use in Palu. The 4th International Conference on Rural Studies in Asia, 331–340. Semarang: KnE Social Sciences. https://doi.org/10.18502/kss.v10i10.18683

DOI: https://doi.org/10.20961/ge.v12i1.96195

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