DOI: https://doi.org/10.14710/jwl.11.1.92-107

Evaluation of Regional Spatial Development on Landslide and Flood Prone with Actual Site Conditions in Kendari City

*Septianto Aldiansyah orcid  -  Departement of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia, Indonesia
Duwi Setiyo Wigati Ningsih  -  Department of Geography, Faculty of Social Science, State University of Malang, Malang, Indonesia, Indonesia
Randi Adrian Saputra  -  Department of Geography Education, Faculty of Teacher Training and Education, Halu Oleo University, Kendari, Indonesia, Indonesia
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Abstract
Kendari City is an area that has a high level of vulnerability to landslides and floods. The high intensity of rainfall and the geomorphological form of the area make Kendari City almost every year landslides and floods occur. This study aims to analyze the distribution of landslide and flood susceptibility and its suitability to the actual situation and evaluate the spatial pattern plan, especially in settlement areas. The method used is survey-based scoring and weighting. Overlay technique used in this study on physical variables including geological conditions, slope, rainfall, land use, soil type and distance from the river. The results show that areas in Kendari City are prone to landslides and floods respectively 79.33% and 81.75% with variations in the level of moderate and high vulnerability. Moderate vulnerability dominates in both disasters with an area of 165.80 km2 and 165.70 km2. The suitability between the map and the actual situation reached 80.63% and 91.30%. Most of the spatial pattern plans, especially settlements that have been made and determined by the government, are appropriate for regional development in Kendari City. Evaluation of spatial patterns of landslide and flood prone zones shows that a small proportion of high vulnerability zones are in the delineation of settlement areas with suitability levels reaching 93.05% and 76.45%.

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Keywords: Suitability, Evaluation of Regional Development, Spatial Planning, Landslide and Flood Prone.

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Section: Research Articles
Language : EN
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  7. Chen, W., Pourghasemi, H. R., Kornejady, A., & Zhang, N. (2017). Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques. Geoderma, 305, 314-327. https://doi.org/10.1016/j.geoderma.2017.06.020
  8. Damanik, M. R. S., & Restu, R. (2012). Pemetaan Tingkat Risiko Banjir dan Longsor Sumatera Utara Berbasis Sistem Informasi Geografis. Jurnal Geografi, 4(1), 29-42. https://doi.org/10.24114/jg.v4i1.7926
  9. Darmawan, K., Hani’ah, H., & Suprayogi, A. (2017). Analisis tingkat kerawanan banjir di kabupaten sampang menggunakan metode overlay dengan scoring berbasis sistem informasi geografis. Jurnal Geodesi Undip, 6(1), 31–40. Retrieved from https://ejournal3.undip.ac.id/index.php/geodesi/article/view/15024
  10. Dewi, T. S., Kusumayudha, S. B., & Purwanto, H. S. (2017). Zonasi Rawan Bencana Tanah Longsor Dengan Metode Analsis GIS: Studi Kasus Daerah Semono dan Sekitarnya Kecamatan Bagelen, Kabupaten Purworejo, Jawa Tengah. Jurnal Mineral, Energi, dan Lingkungan, 1(1), 50-59. https://doi.org/10.31315/jmel.v1i1.1773
  11. Fahmi, F., Sitorus, S. R. ., & Fauzi, A. (2016). Evaluasi Pemanfaatan Penggunaan Lahan Berbasis Rencana Pola Ruang Kota Baubau, Provinsi Sulawesi Tenggara. Tataloka, 18(1), 27. https://doi.org/10.14710/tataloka.18.1.29-46
  12. Faizana, F., Nugraha, A.L., & Yuwono, B.D. (2015). Pemetaan risiko bencana tanah longsor kota semarang. Jurnal Geodesi Undip, 4(1), 223–234. Retrieved from https://ejournal3.undip.ac.id/index.php/geodesi/article/view/7669
  13. Fariza, A., Rusydi, I., Hasim, J. A. N., & Basofi, A. (2017, November). Spatial flood risk mapping in east Java, Indonesia, using analytic hierarchy process—Natural breaks classification. In 2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE) (pp. 406-411). IEEE. doi: 10.1109/ICITISEE.2017.8285539
  14. Hardianto, A., Winardi, D., Rusdiana, D. D., Putri, A. C. E., Ananda, F., Devitasari, Djarwoatmodjo, F. S., Yustika, F., & Gustav, F. (2020). Pemanfaatan Informasi Spasial Berbasis SIG untuk Pemetaan Tingkat Kerawanan Longsor di Kabupaten Bandung Barat, Jawa Barat. Jurnal Geosains Dan Remote Sensing, 1(1), 23–31. https://doi.org/10.23960/jgrs.2020.v1i1.16
  15. Hasnawir, H. (2012). Intensitas Curah Hujan Memicu Tanah Longsor Dangkal Di Sulawesi Selatan. Jurnal Penelitian Kehutanan Wallacea, 1(1), 62. https://doi.org/10.18330/jwallacea.2012.vol1iss1pp62-73
  16. Hutapea, S. (2020). Biophysical Characteristics of Deli River Watershed to Know Potential Flooding in Medan City, Indonesia. Journal of Rangeland Science, 10(3), 316-327
  17. Javidan, N., Kavian, A., Pourghasemi, H. R., Conoscenti, C., Jafarian, Z., & Rodrigo-Comino, J. (2021). Evaluation of multi-hazard map produced using MaxEnt machine learning technique. Scientific reports, 11(1), 1-20. https://doi.org/10.1038/s41598-021-85862-7
  18. Kahal, A. Y., Abdelrahman, K., Alfaifi, H. J., & Yahya, M. M. A. (2021). Landslide hazard assessment of the Neom promising city, northwestern Saudi Arabia: An integrated approach. Journal of King Saud University - Science, 33(2), 101279. https://doi.org/10.1016/j.jksus.2020.101279
  19. Lumban Batu, J. A. J., & Fibriani, C. (2017). Analisis penentuan lokasi evakuasi bencana banjir dengan pemanfaatan sistem informasi geografis dan metode simple additive weighting. Jurnal Teknologi Informasi dan Ilmu Komputer, 4(2), 127. https://doi.org/10.25126/jtiik.201742315
  20. Mandal, B., & Mandal, S. (2018). Analytical hierarchy process (AHP) based landslide susceptibility mapping of Lish river basin of eastern Darjeeling Himalaya, India. Advances in Space Research, 62(11), 3114–3132. https://doi.org/10.1016/j.asr.2018.08.008
  21. Maranguit, D., Guillaume, T., & Kuzyakov, Y. (2017). Effects of flooding on phosphorus and iron mobilization in highly weathered soils under different land-use types: Short-term effects and mechanisms. Catena, 158, 161-170. https://doi.org/10.1016/j.catena.2017.06.023
  22. Nurdin, P. F., Kubota, T., & Soma, A. S. (2019). Investigation of flood and landslide in the Jeneberang catchment area, Indonesia in 2019. International Journal of Erosion Control Engineering, 12(1), 13-18. https://doi.org/10.13101/ijece.12.13
  23. Omukuti, J., Megaw, A., Barlow, M., Altink, H., & White, P. (2021). The value of secondary use of data generated by non-governmental organisations for disaster risk management research: Evidence from the Caribbean. International Journal of Disaster Risk Reduction, 56(January), 102114. https://doi.org/10.1016/j.ijdrr.2021.102114
  24. Pangaribuan, J., Sabri, L. M., & Amarrohman, F. J. (2019). Analisis Daerah Rawan Bencana Tanah Longsor Di Kabupaten Magelang Menggunakan Sistem Informasi Geografis Dengan Metode Standar Nasional Indonesia Dan Analythical Hierarchy Process. Jurnal Geodesi Undip, 8(1), 288–297. Retrieved from https://ejournal3.undip.ac.id/index.php/geodesi/article/view/22582
  25. Pribadi, W. (2021). Kesesuaian Perubahan Penggunaan Tanah Terhadap Rencana Tata Ruang Wilayah Kota Kendari (Doctoral dissertation, Sekolah Tinggi Pertanahan Nasional)
  26. Rahmi, K. I. N., Ali, A., Maghribi, A. A., Aldiansyah, S., & Atiqi, R. (2022). Monitoring of land use land cover change using google earth engine in urban area: Kendari city 2000-2021. In IOP Conference Series: Earth and Environmental Science (Vol. 950, No. 1, p. 012081). IOP Publishing. doi: 10.1088/1755-1315/950/1/012081
  27. Restele, L. O., Hidayat, A., Saleh, F., & Salihin, L. M. (2023). Landslide hazard assessments and their application in land management in Kendari, Southeast Sulawesi Province, Indonesia. Journal of Degraded & Mining Lands Management, 10(3), 4349-4356. doi: 10.15243/jdmlm.2023.103.4349
  28. Sarya, G., Andriawan, A. H., Ridho, A., & Seputro, H. (2014). Intensitas Curah Hujan Memicu Tanah Longsor Dangkal di Desa Wonodadi Kulon. Jurnal Pengabdian LPPM UNTAG Surabaya, 1(1), 65–71
  29. Sihotang, D. M. (2016). Metode Skoring dan Metode Fuzzy dalam Penentuan Zona Resiko Malaria di Pulau Flores. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi (JNTETI), 5(4), 302–308. https://doi.org/10.22146/jnteti.v5i4.278
  30. Srinivas, R., Singh, A. P., Dhadse, K., Garg, C., & Deshmukh, A. (2018). Sustainable management of a river basin by integrating an improved fuzzy based hybridized SWOT model and geo-statistical weighted thematic overlay analysis. Journal of Hydrology, 563(May), 92–105. https://doi.org/10.1016/j.jhydrol.2018.05.059
  31. Sturges, H. A. (1926). The choice of a class interval. Journal of The American Statistical Association, 21(153), 65-66
  32. Sulistio, S., Rondonuwu, D. M., & Poli, H. (2020). ISSN 2442-3262. Jurnal Spasial Vol 7.No.1, 2020. 7(1),164–175
  33. Susanti, P. D., Miardini, A., & Harjadi, B. (2017). Analisis kerentanan tanah longsor sebagai dasar mitigasi di kabupaten banjarnegara (vulnerability analysis as a basic for landslide mitigation in banjarnegara regency). Jurnal Penelitian Pengelolaan Daerah Aliran Sungai (Journal of Watershed Management Research), 1(1), 49-59. https://doi.org/10.20886/jppdas.2017.1.1.49-59
  34. Unisri, P. F. P. (2015). Hubungan Klasifikasi Longsor, Klasifikasi Tanah Rawan Longsor Dan Klasifikasi Tanah Pertanian Rawan Longsor. Gema, 27(49), 61412
  35. Utama, L., & Naumar, A. (2015). Kajian kerentanan kawasan berpotensi banjir bandang dan mitigasi bencana pada daerah aliran sungai (DAS) Batang Kuranji Kota Padang. Rekayasa Sipil, 9(1), 21-28. Retrieved from https://rekayasasipil.ub.ac.id/index.php/rs/article/view/294

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