Spatial Analysis of Ground Movement Potential, Based on Rock Type and Distance from Active Faults in Ambon City, Indonesia
DOI:
https://doi.org/10.18502/kss.v10i10.18675Keywords:
Ambon, active faults, land movement, spatial analysis, rock typesAbstract
Ambon City is one of the most landslide-prone areas in Maluku Province. This study aims to analyze the potential for ground motion in Ambon City, Indonesia, by considering rock types and distance from active faults. This research uses geological data and distance from faults, which are then analyzed using the spatial overlay method. The results showed that the area with high potential for land movement disasters is 8,347.14 ha, medium is 12,157.24 ha, and low is 12,069.09 ha. The predicted built-up area affected in the low class is 2,296.23 ha, in the medium class is 1,470.58 ha, and in the high class is 672.36 ha. These findings highlight the need for special attention to areas with high ground motion potential, as well as the importance of effective mitigation strategies to protect infrastructure and communities. This research is expected to provide useful insights for spatial planning and disaster risk management in Ambon City.
References
BNPB. Indeks Resiko Bencana Indonesia. Jakarta: Badan Nasional Penanggulangan Bencana; 2023. 327 pp.
Ainiyah R, Wibowo A. Analisis Pengaruh Jenis Batuan dan Sesar Aktif Terhadap Potensi Pergerakan Tanah (Studi Kasus: cianjur). J Pendidik Geogr Undiksha [Internet]. 2024 Apr;12(01):23–31. Available from: https://ejournal.undiksha.ac.id/index.php/JJPG/article/view/67230
Rakuasa HR. Pemetaan Kerentana Bencana Tanah Longsor Berbasis Sistem Informasi Geografis Di Kota Ambon. In: Prosiding SN, editor. BIG. Jakarta: BIG & MAPIN; 2021. pp. 327–36. [Internet], Available from http://semnas.big.go.id/index.php/SN/article/view/1148
Yang CH, Stemmler C, Müterthies A. Ground Movement Analysis In Post-Mining City Using Mtinsar With Help Of European Ground Motion Service. ISPRS Ann Photogramm Remote Sens Spat Inf Sci [Internet]. 2023 Dec 5;X-1/W1-202:739–45. Available from: https://isprs-annals.copernicus.org/articles/X-1-W1-2023/739/2023/
Somae G, Supriatna S, Manessa MD, Rakuasa H. SMORPH Application for Analysis of Landslide Prone Areas in Sirimau District, Ambon City. Soc Humanit Educ Stud Conf Ser [Internet]. 2022 Dec 25;5(4):11. Available from: https://jurnal.uns.ac.id/SHES/article/view/68936
Cai Y, Jiang Y, Liu B, Djamaluddin I. Computational implementation of a GIS developed tool for prediction of dynamic ground movement and deformation due to underground extraction sequence [Internet]. Int J Coal Sci Technol. 2016 Dec;3(4):379–98. Available from: http://link.springer.com/10.1007/s40789-016-0151-0
Shinohara Y, Kume T. Changes in the factors contributing to the reduction of landslide fatalities between 1945 and 2019 in Japan [Internet]. Sci Total Environ. 2022 Jun;827:154392. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0048969722014851
Abay A, Barbieri G, Woldearegay K. GIS-based Landslide Susceptibility Evaluation Using Analytical Hierarchy Process (AHP) Approach: The Case of Tarmaber District, Ethiopia [Internet]. Momona Ethiop J Sci. 2019 May;11(1):14. Available from: https://www.ajol.info/index.php/mejs/article/view/186815
Ullah F. Su L jun, Cheng L, Alam M. Landslide Hazard Assessment and Runout Simulation by Utilizing Remote Sensing, Geophysical, and Geological Techniques [Internet]. Research Square; 2022. Available from: http://europepmc.org/abstract/PPR/PPR440369
Susetyo JA, Kurnianto FA, Nurdin EA, Pangastuti EI. Landslide Disaster Mapping in Silo District, Jember Regency. {IOP} Conf Ser Earth Environ Sci [Internet]. 2022 Jan;975(1):12011. Available from: https://doi.org/10.1088/1755-1315/975/1/012011.
Li C, Fu Z, Wang Y, Tang H, Yan J, Gong W, et al. Susceptibility of reservoir-induced landslides and strategies for increasing the slope stability in the Three Gorges Reservoir Area: zigui Basin as an example. Eng Geol. 2019;261(August):105279.
Ram P, Gupta V. Landslide hazard, vulnerability, and risk assessment (HVRA), Mussoorie township, lesser himalaya, India [Internet]. Environ Dev Sustain. 2022;24(1):473–501.
Mirdda HA, Bera S, Chatterjee R. Vulnerability assessment of moun- tainous households to landslides: A multidimensional study in the rural Himalayas [Internet]. Int J Disaster Risk Reduct. 2022;71:102809. Available from: https://www.sciencedirect.com/science/article/pii/S2212420922000280
Aditian A, Kubota T, Shinohara Y. Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a ter- tiary region of Ambon, Indonesia [Internet]. Geomorphology. 2018;318:101–11. Available from: https://www.sciencedirect.com/science/article/pii/S0169555X16304470
Hehanussa FS, Latue PC, Rakuasa H, Somae G. Integration of Remote Sensing Data and Geographic Information System for Mapping Landslide Risk Areas in Ambon City, Indonesia. J Selvic Asean [Internet]. 2024;1(3):105–19. Available from: https://journal.ypidathu.or.id/index.php/selvicoltura/article/view/1185
Rakuasa H, Rifai A. Pemetaan Kerentanan Bencana Tanah Longsor Berbasis Sistem Informasi Geografis di Kota Ambon. Seminar Nasional Geomatika Tahun 2021. Badan Informasi Geospasial; 2021. pp. 327–36.
Rosyidy MK, Dimyati IM, Shidiq IP, Zulkarnain F, Rahaningtyas NS, Syamsuddin RP, et al. Landslide Surface Deformation Analysis Using SBAS-INSAR In The Southern Part of The Sukabumi Area, Indonesia. Geogr Tech [Internet]. 2021 Sep 15;(Spe- cial Issue):138–52. Available from: http://technicalgeography.org/index.php/on-line- first/393-11_rosyidy
Souisa M, Hendrajaya L, Handayani G. Landslide hazard and risk assess- ment for Ambon city using landslide inventory and geographic information system [Internet]. J Phys Conf Ser. 2016 Aug;739:012078. Available from: https://iopscience.iop.org/article/10.1088/1742-6596/739/1/012078
Rakuasa, H., Supriatna, S., Tambunan., M,P., Salakory, M., Pinoa, W S. Analisis Spasial Daerah Potensi Rawan Longsor di Kota Ambon Dengan Menggunakan Metode SMORPH. J Tanah dan Sumberd Lahan. 2022;9(2):213–21.
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 KnE Social Sciences

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