Soil-Geomorphological Mapping Using Landsat-9 Imagery and GIS in West Muna Regency, Indonesia

Tahir Tahir, Daud Yusuf

Abstract


Accurate soil-type information is essential for land-resource planning, yet spatial soil data for West Muna Regency remain limited for supporting land-use zoning. Recent advances in remote sensing and geographic information systems (GIS) have strengthened soil mapping by enabling more efficient acquisition, processing, analysis, and presentation of spatial data. This study applies integrated remote sensing and GIS, supported by a soil-geomorphological approach, to identify and map the spatial distribution of soil characteristics in West Muna Regency. The objectives of this study are to identify soil-type distribution, analyze soil texture and surface-drainage patterns, and interpret these characteristics in relation to geomorphological units and land-use planning needs. Landsat-9 imagery was interpreted together with landform analysis, GIS-based spatial overlay, field observation, and laboratory analysis of soil characteristics. The results show that soils in West Muna Regency are classified into three soil orders: Inceptisols, Alfisols, and Entisols. Swampy alluvial plains and coastal alluvial plains are dominated by relatively fertile sandy clay soils, whereas rocky coastal areas are characterized mainly by marine sand deposits with lower nutrient status. Spatial analysis indicates that Inceptisols occupy the largest area, covering 71,250.04 ha or 78.65% of the regency, followed by Alfisols with 11,923.42 ha or 13.16%, and Entisols with 7,414.15 ha or 8.18% of total area. These findings indicate that soil distribution is closely related to landform, parent material, soil texture, and drainage condition. The integrated soil-geomorphological approach provides practical spatial information for regional soil-resource assessment and land-use planning in West Muna Regency.

Keywords


GIS; Landsat-9; Soil Drainage; Soil Texture; Soil-Geomorphological Mapping

Full Text:

PDF

References


Ait Ben Ahmed, H., Ezzahar, J., Er-Raki, S., Khabba, S., Merlin, O., Elfarkh, J., Bouswir, Z., Bouljihel, S., Aouade, G., & Chehbouni, A. (2026). Surface soil moisture and land surface temperature as constraints for multi-objective calibration of a dual-source SVAT model over semi-arid irrigated winter wheat. Agricultural Water Management, 330, 110426. https://doi.org/10.1016/j.agwat.2026.110426

Blume, H.-P., Beyer, L., Kalk, E., & Kuhn, D. (2002). Weathering and soil formation. In Geoecology of Antarctic ice-free coastal landscapes (pp. 115–138). Springer.

Chen, Z., Ma, A., Wang, J., Zhou, Y., Zhong, Y., & Zhang, L. (2026). Task-driven remote sensing image captioning for earth understanding: From multi-task dataset to task-conditioned framework. ISPRS Journal of Photogrammetry and Remote Sensing, 238, 679–692. https://doi.org/10.1016/j.isprsjprs.2026.05.024

Dobrovol'skaya, T. G., Zvyagintsev, D. G., Chernov, I. Y., Golovchenko, A. V., Zenova, G. M., Lysak, L. V., Manucharova, N. A., Marfenina, O. E., Polyanskaya, L. M., Stepanov, A. L., & Umarov, M. M. (2015). The role of microorganisms in the ecological functions of soils. Eurasian Soil Science, 48, 959–967. https://doi.org/10.1134/S1064229315090033

Frye, C., Sayre, R., Murphy, A. B., Karagülle, D., Pippi, M., Gilbert, M., & Richards, J. W. (2023). Named Landforms of the World: A Geomorphological and Physiographic Compilation. Annals of the American Association of Geographers, 113(8), 1762–1780. https://doi.org/10.1080/24694452.2023.2200548

Gerasimova, M. I., Ananko, T. V., & Savitskaya, N. V. (2020). Approaches to the introduction of human-modified soils in the updated version of the soil map of Russia, 1:2.5 M scale: By the example of Moscow Oblast. Eurasian Soil Science, 53(1), 16–26. https://doi.org/10.1134/S1064229320010081

Johnson, N. C., Miller, R. M., & Wilson, G. W. T. (2017). Mycorrhizal interactions with climate, soil parent material, and topography. In Mycorrhizal mediation of soil: Fertility, structure, and carbon storage (pp. 47–66). Elsevier. https://doi.org/10.1016/B978-0-12-804312-7.00004-8

Kalev, S. D., & Toor, G. S. (2018). The composition of soils and sediments. In Green chemistry: An inclusive approach (pp. 339–357). Elsevier. https://doi.org/10.1016/B978-0-12-809270-5.00014-5

Kaliraj, S., Adhikari, K., Dharumarajan, S., Lalitha, M., & Kumar, N. (2024). Remote sensing and geographic information system applications in mapping and assessment of soil resources. In Remote sensing of soils: Mapping, monitoring, and measurement (pp. 25–41). Elsevier. https://doi.org/10.1016/B978-0-443-18773-5.00014-4

Kaliraj, S., Kiruthika, N., Vairaveni, E., & Palanivel, K. (2025). Landsat 9 OLI/TIRS image-derived soil properties as a tool to evaluate soil quality zone using GIS-based AHP technique: A case study of Thamirabarani River Basin, Southern India. In Sustainable agriculture management in semi-arid climates: Volume 1 (pp. 217–248). Springer. https://doi.org/10.1007/978-3-031-94062-0_11

Karfidova, E. A., & Makeev, V. M. (2026). Geomorphometric methods for analyzing inherited uplift and erosion and denudation processes in the Moscow territory. In Structural geology, geoenvironment and geodynamic (pp. 245–254). Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-105035044139&partnerID=40&md5=308798acca48ec0b63146ed165caa023

Li, L., Jiang, Y., & Shen, X. (2026). On-orbit relative radiometric calibration of remote sensing satellite planar array sensors with geometric constraints and multi-scale radiometric cascades. ISPRS Journal of Photogrammetry and Remote Sensing, 238, 356–378. https://doi.org/10.1016/j.isprsjprs.2026.05.014

Li, Y., Long, Y., Liu, T., Zhang, D., He, M., Xie, Q., & Zhang, Z. (2025). The role of soil microorganisms and physicochemical properties in determining the germinate of invasive Solidago canadensis L. Plant and Soil, 507, 897–914. https://doi.org/10.1007/s11104-024-06776-7

Liu, F., Rossiter, D. G., Zhang, G.-L., & Li, D.-C. (2020). A soil colour map of China. Geoderma, 379, Article 114556. https://doi.org/10.1016/j.geoderma.2020.114556

Martin Thiagaraja, S., Govindaraji, S., Meena, S., Balachandar, D., Thangamani, C., & Surendran, U. (2025). Carbon Stability, Clay Mineral Interactions, and Organic Matter in Long-Term Fertilizer Experiments. Communications in Soil Science and Plant Analysis, 56(15), 2365–2376. https://doi.org/10.1080/00103624.2025.2505428

Mashimbye, Z. E., & Loggenberg, K. (2023). A Scoping Review of Landform Classification Using Geospatial Methods. Geomatics, 3(1), 93-114. https://doi.org/10.3390/geomatics3010005

Muthulakshmi, S., Backiyavathy, M.R., Gopalakrishnan, M., Kalpana, R., Thangamani, C., & Pavithra, S.I. (2024). Insights of Machine Learning Approach for Soil Fertility Assessment and Management Strategy. Communications in Soil Science and Plant Analysis, 56, 436 - 457. https://doi.org/10.1080/00103624.2024.2416920

Paraforos, D. S., Muzirafuti, A., Randazzo, G., & Lanza, S. (Eds.). (2022). Sustainable agriculture and advances of remote sensing (Vol. 2). MDPI. https://doi.org/10.3390/books978-3-0365-5336-8

Okur, B., & Örçen, N. (2020). Soil salinization and climate change. In Climate change and soil interactions (pp. 331–350). Elsevier. https://doi.org/10.1016/B978-0-12-818032-7.00012-6

Polyakov, V., Kartoziia, A., Nizamutdinov, T., Wang, W., & Abakumov, E. (2022). Soil-geomorphological mapping of Samoylov Island based on UAV imaging. Frontiers in Environmental Science, 10, Article 948367. https://doi.org/10.3389/fenvs.2022.948367

Priya, M., Bhatt, D. P., & Malche, T. (2026). Smart soil systems: Bridging soil classification, precision farming, and digital agriculture in India. In Computational techniques in precision agriculture: Advances and applications (pp. 250–260). CRC Press. https://doi.org/10.1201/9781003520733

Roma, E., & Catania, P. (2026). UAV remote sensing for fertilization rating in olive groves. In Smart agriculture: Concepts, strategies, and case studies (pp. 74–94). CRC Press. https://doi.org/10.1201/9781003510598-5

Skorupa, A. L., Silva, S. H., Poggere, G. C., Tassinari, D., Pinto, L. C., & Curi, N. (2017). Similar soils but different soil-forming factors: Converging evolution of Inceptisols in Brazil. Pedosphere, 27(4), 747–757. https://doi.org/10.1016/S1002-0160(17)60443-0

Sung, C. T. B., Ishak, C. F., Abdullah, R., Othman, R., Panhwar, Q. A., & Aziz, M. M. A. (2017). Soil properties: Physical, chemical, biological, mechanical. Soils of Malaysia, 22, 103–154. https://doi.org/10.1201/9781315277189-6

Tong, Y., Xiang, H., Jiang, J., & Chen, W. (2024). Interfacial interactions between minerals and organic matter: Mechanisms and characterizations. Chemosphere, 359, 142383. https://doi.org/10.1016/j.chemosphere.2024.142383

Wilson, M. (2019). The importance of parent material in soil classification: A review in a historical context. Catena, 182, 104131. https://doi.org/10.1016/j.catena.2019.104131

Yusuf, D., & Indrawan. (2019). Analysis of Seagrass Condition Using Spectral Reflection of Quickbird Imagery on Saronde Island North Gorontalo. Jambura Geoscience Review, 1(1), 1-6. https://doi.org/10.34312/jgeosrev.v1i1.2015

Zhang, J., Zeng, S., Shi, W., Namaiti, A., Song, Y., Tian, J., & Ji, D. (2026). Identifying urban morphological archetypes using k-means to analyze spatial heterogeneity of the urban thermal environment. City and Environment Interactions, 30, 100356. https://doi.org/10.1016/j.cacint.2026.100356




DOI: https://doi.org/10.37905/jgeosrev.v8i2.39798

Bookmark and Share


Copyright (c) 2026 Daud Yusuf, Tahir Tahir

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.