DOI: https://doi.org/10.14710/geoplanning.12.2.%25p

Urban Flood Susceptibility Analysis Using Multi Criteria Decision Analytical Hierarchy Process (AHP) Method: Case Study of Bandung City

Rena Denya Agustina scopus  -  Department of Physics Education, Faculty of Tarbiyah and Teaching, UIN Sunan Gunung Djati Bandung, Indonesia
*Riki Purnama Putra orcid scopus  -  Master's Program in Geodesy and Geomatics Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Indonesia
Seni Susanti scopus  -  Department of Physics Education, Faculty of Tarbiyah and Teaching, UIN Sunan Gunung Djati Bandung, Indonesia
Agustinus Bambang Setyadji scopus  -  Master's Program in Geodesy and Geomatics Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Indonesia
Riantini Virtriana scopus  -  Master's Program in Geodesy and Geomatics Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Indonesia

Citation Format:
Abstract

Flood is one of the natural disasters and is supported by bad human habits, of course, this disaster can cause enormous losses, which can take lives. Flood handling certainly requires proper analysis before handling is carried out. Various methods for mapping flood susceptibility can be done, one of which is using the AHP Multi-Criteria Decision method which is considered the most up-to-date and very accurate method in terms of accuracy. This study aims to map the susceptibility of flood hazard in urban areas, especially in the city of Bandung with the help of satellite imagery. The method in this study uses the AHP Multi-Criteria Decision method, where five experts are needed to carry out an assessment in determining the variable weight value, with the variable in question namely; (1) TWI; (2) Elevations; (3) Slopes; (4) Precipitation; (5) Land Cover; (6) NDVI; (7) Distance from Rivers; and (8) Distance from Roads. In addition, this study validates the results of the mapping by comparing the real events of flooding in the city of Bandung in 2002-2022 with the map of the susceptibility of flood hazard in the city of Bandung. The results obtained in this study are flood hazard susceptibility maps created well with validation of 80.2%. In addition, areas that are very at hazard of being affected by flooding are the East Bandung area (Mandalajati, Ujungberung, Cibiru, Gedebage, and Panyileukan) with a high hazard of over 75%, and an extreme hazard of above 0.1%.

Fulltext
Keywords: AHP, Flood, GIS, Multi-Criteria Decision, Probability
Funding: LITAPDIMAS KEMENAG and LP2M UIN Sunan Gunung Djati Bandung

Article Metrics:

Article Info
Section: Original Research
Language : EN
Recent articles
Integration of AHP and GIS to derive Walkability Index for Women to Access Rail-Transit Station Spatial Upgrading of Riverbank Slums towards Sustainability of Watershed Infrastructure Empirical Evidence of Environmental Degradation Using Geospatial Technology in Tasik Temenggor, Royal Belum Perak, Malaysia More recent articles
Most cited articles
GIS-BASED ANALYSIS FOR ASSESSING LANDSLIDE AND DROUGHT HAZARD IN THE CORRIDOR OF MT. MERAPI AND MT. MERBABU NATIONAL PARK, INDONESIA MODEL OF CLIMATE AND LAND-USE CHANGES IMPACT ON WATER SECURITY IN AMBON CITY, INDONESIA SLUM REVITALIZING PLAN OF BAGHDADIYAH BY SPATIAL RE-MODELING CONFIGURATION QUALITY ANALYSIS OF SINGLE TREE OBJECT WITH OBIA AND VEGETATION INDEX FROM LAPAN SURVEILLANCE AIRCRAFT MULTISPECTRAL DATA IN URBAN AREA A GIS BASED EVALUATION OF LAND USE CHANGES AND ECOLOGICAL CONNECTIVITY INDEX More cited articles

  1. Abbott, M. J. O. (2024). Fragile New Orleans, Fortress New Orleans: Navigating Flood Risk Management in a Below-Sea-Level City. Cornell University.

  2. Abdullah, M. F., Siraj, S., & Hodgett, R. E. (2021). An Overview of Multi-Criteria Decision Analysis (MCDA) Application in Managing Water-Related Disaster Events: Analyzing 20 Years of Literature for Flood and Drought Events. Water, 13(10), 1358. https://doi.org/10.3390/w13101358">[Crossref]

  3. Abebe, Y. A., Ghorbani, A., Nikolic, I., Vojinovic, Z., & Sanchez, A. (2019). A Coupled Flood-Agent-Institution Modelling (CLAIM) Framework for Urban Flood Risk Management. Environmental Modelling & Software, 111, 483–492. https://doi.org/10.1016/j.envsoft.2018.10.015">[Crossref]

  4. Adnan, M. S. G., Dewan, A., Zannat, K. E., & Abdullah, A. Y. M. (2019). The Use of Watershed Geomorphic Data in Flash Flood Susceptibility Zoning: A Case Study of the Karnaphuli and Sangu River Basins of Bangladesh. Natural Hazards, 99(1), 425–448. https://doi.org/10.1007/s11069-019-03749-3">[Crossref]

  5. Al-Juaidi, A. E. M., Nassar, A. M., & Al-Juaidi, O. E. M. (2018). Evaluation of Flood Susceptibility Mapping using Logistic Regression and GIS Conditioning Factors. Arabian Journal of Geosciences, 11(24), 765. https://doi.org/10.1007/s12517-018-4095-0">[Crossref]

  6. Althuwaynee, O. F., Pradhan, B., & Lee, S. (2016). A Novel Integrated Model for Assessing Landslide Susceptibility Mapping Using CHAID and AHP Pair-Wise Comparison. International Journal of Remote Sensing, 37(5), 1190–1209. https://doi.org/10.1080/01431161.2016.1148282">[Crossref]

  7. Anelli, D., Tajani, F., & Ranieri, R. (2022). Urban Resilience Against Natural Disasters: Mapping the Risk with an Innovative Indicators-based Assessment Approach. Journal of Cleaner Production, 371, 133496. https://doi.org/10.1016/j.jclepro.2022.133496">[Crossref]

  8. Berndtsson, R., Becker, P., Persson, A., Aspegren, H., Haghighatafshar, S., Jönsson, K., Larsson, R., Mobini, S., Mottaghi, M., & Nilsson, J. (2019). Drivers of changing urban flood risk: A framework for action. Journal of Environmental Management, 240, 47–56.

  9. Bertilsson, L., Wiklund, K., de Moura Tebaldi, I., Rezende, O. M., Veról, A. P., & Miguez, M. G. (2019). Urban Flood Resilience – A Multi-Criteria Index to Integrate Flood Resilience Into Urban Planning. Journal of Hydrology, 573, 970–982. https://doi.org/10.1016/j.jhydrol.2018.06.052">[Crossref]

  10. Boulomytis, V. T. G., Zuffo, A. C., & Imteaz, M. A. (2022). Assessment of Flood Susceptibility in Coastal Peri-Urban Areas: an Alternative MCDA Approach for Ungauged Catchments. Urban Water Journal, 1–13. https://doi.org/10.1080/1573062X.2022.2162424">[Crossref]

  11. Bozorgi-Amiri, A., & Asvadi, S. (2015). A Prioritization Model for Locating Relief Logistic Centers Using Analytic Hierarchy Process with Interval Comparison Matrix. Knowledge-Based Systems, 86, 173–181. https://doi.org/10.1016/j.knosys.2015.06.005">[Crossref]

  12. BPS. (2021). Jumlah Kelurahan yang Mengalami Bencana Alam Banjir Menurut Kecamatan di Kota Bandung, 2018, 2019, dan 2020. BPS. https://bandungkota.bps.go.id/statictable/2021/05/21/1484/jumlah-kelurahan-yang-mengalami-bencana-alam-banjir-menurut-kecamatan-di-kota-bandung-2018-2019-dan-2020.html">    

  13. BPS. (2023). Jumlah Penduduk Hasil Proyeksi Interim di Provinsi Jawa Barat Menurut Kabupaten/Kota dan Jenis Kelamin (Orang) Tahun 2021-2023. BPS. https://jabar.bps.go.id/indicator/12/731/1/jumlah-penduduk-hasil-proyeksi-interim-di-provinsi-jawa-barat-menurut-kabupaten-kota-dan-jenis-kelamin.html">  

  14. Cabrera, J. S., & Lee, H. S. (2019). Flood-Prone Area Assessment Using GIS-Based Multi-Criteria Analysis: A Case Study in Davao Oriental, Philippines. Water, 11(11), 2203. https://doi.org/10.3390/w11112203">[Crossref]

  15. Chourabi, Z., Khedher, F., Babay, A., & Cheikhrouhou, M. (2019). Multi-Criteria Decision Making in Workforce Choice Using AHP, WSM and WPM. The Journal of The Textile Institute, 110(7), 1092–1101. https://doi.org/10.1080/00405000.2018.1541434">[Crossref]

  16.  De Moel, H., Jongman, B., Kreibich, H., Merz, B., Penning-Rowsell, E., & Ward, P. J. (2015). Flood risk assessments at different spatial scales. Mitigation and Adaptation Strategies for Global Change, 20(6), 865–890. https://doi.org/10.1007/s11027-015-9654-z">[Crossref]

  17. Dikau, R. (2020). The Application of a Digital Relief Model to Landform Analysis in Geomorphology. In Three dimensional applications in GIS (pp. 51–77). CRC Press.

  18. Doorga, J. R. S., Magerl, L., Bunwaree, P., Zhao, J., Watkins, S., Staub, C. G., Rughooputh, S. D. D. V., Cunden, T. S. M., Lollchund, R., & Boojhawon, R. (2022). GIS-based Multi Criteria Modelling of Flood Risk Susceptibility in Port Louis, Mauritius: Towards Resilient Flood Management. International Journal of Disaster Risk Reduction, 67, 102683. https://doi.org/10.1016/j.ijdrr.2021.102683">[Crossref]

  19. Feng, B., Wang, J., Zhang, Y., Hall, B., & Zeng, C. (2020). Urban Flood Hazard Mapping Using a Hydraulic–GIS Combined Model. Natural Hazards, 100(3), 1089–1104. https://doi.org/10.1007/s11069-019-03850-7">[Crossref]

  20. Ferrini, F., Fini, A., Mori, J., & Gori, A. (2020). Role of Vegetation as a Mitigating Factor in the Urban Context. Sustainability, 12(10), 4247. https://doi.org/10.3390/su12104247">[Crossref]

  21. Ha-Mim, N. M., Rahman, M. A., Hossain, M. Z., Fariha, J. N., & Rahaman, K. R. (2022). Employing Multi-Criteria Decision Analysis and Geospatial Techniques to Assess Flood Risks: A Study of Barguna District in Bangladesh. International Journal of Disaster Risk Reduction, 77, 103081. https://doi.org/10.1016/j.ijdrr.2022.103081">[Crossref]

  22. Hadipour, V., Vafaie, F., & Deilami, K. (2020). Coastal Flooding Risk Assessment Using a GIS-Based Spatial Multi-Criteria Decision Analysis Approach. Water, 12(9), 2379. https://doi.org/10.3390/w12092379">[Crossref]

  23. Hamel, P., & Tan, L. (2022). Blue–Green Infrastructure for Flood and Water Quality Management in Southeast Asia: Evidence and Knowledge Gaps. Environmental Management, 69(4), 699–718. https://doi.org/10.1007/s00267-021-01467-w">[Crossref]

  24. Harris, I., Osborn, T. J., Jones, P., & Lister, D. (2020). Version 4 of the CRU TS Monthly High-Resolution Gridded Multivariate Climate Dataset. Scientific Data, 7(1), 109. https://doi.org/10.1038/s41597-020-0453-3">[Crossref]

  25. Hasanloo, M., Pahlavani, P., & Bigdeli, B. (2019). Flood Risk Zonation Using a Multi-Criteria Spatial Group Fuzzy-AHP Decision Making and Fuzzy Overlay Analysis. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4/W18, 455–460. https://doi.org/10.5194/isprs-archives-XLII-4-W18-455-2019">[Crossref]

  26. Hosseiny, H., Nazari, F., Smith, V., & Nataraj, C. (2020). A Framework for Modeling Flood Depth Using a Hybrid of Hydraulics and Machine Learning. Scientific Reports, 10(1), 8222. https://doi.org/10.1038/s41598-020-65232-5">[Crossref]

  27. Idris, I. S. W. (2022). Implementasi Kebijakan Peraturan Daerah No. 83 Tahun 2018 Tentang Kebijakan dan Strategi Kabupaten Sumenep dalam Pengelolaan Sampah Rumah Tangga dan Sampah Sejenis Sampah Rumah Tangga (Studi di Desa Pinggir Papas Kecamatan Kalianget) [Universitas wiraraja Madura]. http://repository.wiraraja.ac.id/id/eprint/2709">  

  28. Karunia, T. U., Ersa, N. S., & Ikhwali, M. F. (2021). Flood Control Strategy in Kali Sabi River Basin in Tangerang. IOP Conference Series: Earth and Environmental Science, 871(1), 012043. https://doi.org/10.1088/1755-1315/871/1/012043">[Crossref]

  29. Khosravi, K., Panahi, M., Golkarian, A., Keesstra, S. D., Saco, P. M., Bui, D. T., & Lee, S. (2020). Convolutional Neural Network Approach for Spatial Prediction of Flood Hazard at National Scale of Iran. Journal of Hydrology, 591, 125552. https://doi.org/10.1016/j.jhydrol.2020.125552">[Crossref]

  30. Lin, C., & Kou, G. (2015). Bayesian Revision of the Individual Pair-Wise Comparison Matrices Under Consensus in AHP–GDM. Applied Soft Computing, 35, 802–811. https://doi.org/10.1016/j.asoc.2015.02.041">[Crossref]

  31. Liu, J., Shao, W., Xiang, C., Mei, C., & Li, Z. (2020). Uncertainties of Urban Flood Modeling: Influence of Parameters for Different Underlying Surfaces. Environmental Research, 182, 108929. https://doi.org/10.1016/j.envres.2019.108929">[Crossref]

  32. Machado, R. A. S., Oliveira, A. G., & Lois-González, R. C. (2019). Urban Ecological Infrastructure: The Importance of Vegetation Cover in the Control of Floods and Landslides in Salvador / Bahia, Brazil. Land Use Policy, 89, 104180. https://doi.org/10.1016/j.landusepol.2019.104180">[Crossref]

  33. Maragno, D., Gaglio, M., Robbi, M., Appiotti, F., Fano, E. A., & Gissi, E. (2018). Fine-Scale Analysis of Urban Flooding Reduction from Green Infrastructure: An Ecosystem Services Approach for the Management of Water Flows. Ecological Modelling, 386, 1–10. https://doi.org/10.1016/j.ecolmodel.2018.08.002">[Crossref]

  34. Maskrey, S. A., Mount, N. J., & Thorne, C. R. (2022). Doing Flood Risk Modelling Differently: Evaluating the Potential for Participatory Techniques to Broaden Flood Risk Management Decision‐Making. Journal of Flood Risk Management, 15(1). https://doi.org/10.1111/jfr3.12757">[Crossref]

  35. Mensah, H., & Ahadzie, D. K. (2020). Causes, Impacts and Coping Strategies of Floods in Ghana: A Systematic Review. SN Applied Sciences, 2(5), 792. https://doi.org/10.1007/s42452-020-2548-z">[Crossref]

  36. Mignot, E., Li, X., & Dewals, B. (2019). Experimental Modelling of Urban Flooding: A Review. Journal of Hydrology, 568, 334–342. https://doi.org/10.1016/j.jhydrol.2018.11.001">[Crossref]

  37. Morales-Ruano, J. V., Reyes-Umaña, M., Sandoval-Vázquez, F. R., Arellano-Wences, H. J., González-González, J., & Rodríguez-Alviso, C. (2022). Flood Susceptibility in the Lower Course of the Coyuca River, Mexico: A Multi-Criteria Decision Analysis Model. Sustainability, 14(19), 12544. https://doi.org/10.3390/su141912544">[Crossref]

  38. Motta, M., de Castro Neto, M., & Sarmento, P. (2021). A Mixed Approach for Urban Flood Prediction Using Machine Learning and GIS. International Journal of Disaster Risk Reduction, 56, 102154. https://doi.org/10.1016/j.ijdrr.2021.102154">[Crossref]

  39. Msabi, M. M., & Makonyo, M. (2021). Flood Susceptibility Mapping Using GIS and Multi-Criteria Decision Analysis: A Case of Dodoma Region, Central Tanzania. Remote Sensing Applications: Society and Environment, 21, 100445. https://doi.org/10.1016/j.rsase.2020.100445">[Crossref]

  40. Nkwunonwo, U.C., Whitworth, M., & Baily, B. (2020). A Review of the Current Status of Flood Modelling for Urban Flood Risk Management in the Developing Countries. Scientific African, 7, e00269. https://doi.org/10.1016/j.sciaf.2020.e00269">[Crossref]

  41. Nkwunonwo, Ugonna C, Whitworth, M., & Baily, B. (2016). A Review and Critical Analysis of the Efforts Towards Urban Flood Risk Management in the Lagos Region of Nigeria. Natural Hazards and Earth System Sciences, 16(2), 349–369. https://doi.org/10.5194/nhess-16-349-2016">[Crossref]

  42. Nsangou, D., Kpoumié, A., Mfonka, Z., Ngouh, A. N., Fossi, D. H., Jourdan, C., Mbele, H. Z., Mouncherou, O. F., Vandervaere, J.-P., & Ndam Ngoupayou, J. R. (2022). Urban Flood Susceptibility Modelling Using AHP and GIS Approach: Case of the Mfoundi Watershed at Yaoundé in the South-Cameroon Plateau. Scientific African, 15, e01043. https://doi.org/10.1016/j.sciaf.2021.e01043">[Crossref]

  43. O’Donnell, E. C., & Thorne, C. R. (2020). Drivers of Future Urban Flood Risk. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 378(2168), 20190216. https://doi.org/10.1098/rsta.2019.0216">[Crossref]

  44. Piątek, Ł., & Wojnowska-Heciak, M. (2020). Multicase Study Comparison of Different Types of Flood-Resilient Buildings (Elevated, Amphibious, and Floating) at the Vistula River in Warsaw, Poland. Sustainability, 12(22), 9725. https://doi.org/10.3390/su12229725">[Crossref]

  45. Putra, R. P., Agustina, R. D., Qurratu’Aini, K., & Adwasyifa, K. (2022). Analysis of Vegetation Density and Surface Temperature in Buahbatu District, Bandung using Landsat 8 Oli/Tirs Satellite Images. Jurnal Fisika Dan Aplikasinya, 18(3), 63. https://doi.org/10.12962/j24604682.v18i3.12739">[Crossref]

  46. Quattrochi, D. A., Lam, N. S.-N., Qiu, H.-L., & Zhao, W. (2023). Image Characterization and Modeling System (ICAMS): A Geographic Information System for the Characterization and Modeling of Multiscale Remote Sensing Data. In Scale in remote sensing and GIS (pp. 295–307). Routledge.

  47. Rafiei-Sardooi, E., Azareh, A., Choubin, B., Mosavi, A. H., & Clague, J. J. (2021). Evaluating Urban Flood Rrisk Using Hybrid Method of TOPSIS and Machine Learning. International Journal of Disaster Risk Reduction, 66, 102614. https://doi.org/10.1016/j.ijdrr.2021.102614">[Crossref]

  48. Rahmati, O., Pourghasemi, H. R., & Zeinivand, H. (2016). Flood Susceptibility Mapping Using Frequency Ratio and Weights of Evidence Models in the Golastan Province, Iran. Geocarto International, 31(1), 42–70. https://doi.org/10.1080/10106049.2015.1041559">[Crossref]

  49. Rincón, D., Khan, U. T., & Armenakis, C. (2018). Flood Risk Mapping Using GIS and Multi-Criteria Analysis: A Greater Toronto Area Case Study. Geosciences, 8(8), 275. https://doi.org/10.3390/geosciences8080275">[Crossref]

  50. Shahiri Tabarestani, E., & Afzalimehr, H. (2021). A Comparative Assessment of Multi-Criteria Decision Analysis for Flood Susceptibility Modelling. Geocarto International, 1–24. https://doi.org/10.1080/10106049.2021.1923834">[Crossref]

  51. Singh, P., Sinha, V. S. P., Vijhani, A., & Pahuja, N. (2018). Vulnerability Assessment of Urban Road Network from Urban Flood. International Journal of Disaster Risk Reduction, 28, 237–250. https://doi.org/10.1016/j.ijdrr.2018.03.017">[Crossref]

  52. Supriadi, A., & Oswari, T. (2020). Analysis of Geographical Information System (GIS) Design Aplication in the Fire Department of Depok City. 2, 1–9.

  53. Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2015). Flood Susceptibility Analysis and its Verification Using a Novel Ensemble Support Vector Machine and Frequency Ratio Method. Stochastic Environmental Research and Risk Assessment, 29(4), 1149–1165. https://doi.org/10.1007/s00477-015-1021-9">[Crossref]

  54. Vignesh, K. S., Anandakumar, I., Ranjan, R., & Borah, D. (2021). Flood Vulnerability Assessment Using an Integrated Approach of Multi-Criteria Decision-Making Model and Geospatial Techniques. Modeling Earth Systems and Environment, 7(2), 767–781. https://doi.org/10.1007/s40808-020-00997-2">[Crossref]

  55. Wijaya, H. B., & Buchori, I. (2022). Reclassification of urban growth in rural area, Temanggung Regency, Indonesia. Geoplanning: Journal of Geomatics and Planning, 9(1), 1–16. https://doi.org/10.14710/geoplanning.9.1.1-16">[Crossref]

  56. Wing, O. E. J., Bates, P. D., Sampson, C. C., Smith, A. M., Johnson, K. A., & Erickson, T. A. (2017). Validation of a 30 m resolution flood hazard model of the conterminous U nited S tates. Water Resources Research, 53(9), 7968–7986.

  57. Young, A. F., & Papini, J. A. J (2020). How Can Scenarios on Flood Disaster Risk Support Urban Response? A Case Study in Campinas Metropolitan Area (São Paulo, Brazil). Sustainable Cities and Society, 61, 102253. https://doi.org/10.1016/j.scs.2020.102253">[Crossref]

  58. Zambrano, L., Pacheco-Muñoz, R., & Fernández, T. (2018). Influence of Solid Waste and Topography on Urban Floods: The Case of Mexico City. Ambio, 47(7), 771–780. https://doi.org/10.1007/s13280-018-1023-1">[Crossref]

  59. Zhou, Q., Leng, G., Su, J., & Ren, Y. (2019). Comparison of Urbanization and Climate Change Impacts on Urban Flood Volumes: Importance of Urban Planning and Drainage Adaptation. Science of The Total Environment, 658, 24–33. https://doi.org/10.1016/j.scitotenv.2018.12.184">[Crossref] 


Last update:

No citation recorded.

Last update: 2025-12-13 12:38:25

No citation recorded.