Research Article
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3D city model for monitoring flash flood risks in Salalah, Oman

Year 2022, Volume: 7 Issue: 1, 17 - 23, 15.02.2022
https://doi.org/10.26833/ijeg.857971

Abstract

This paper investigates the issues and challenges in using a 3D city model for monitoring flash flood risks in Salalah (Oman) designed using the City Geography Markup Language (CityGML) standards version 2.0. The investigation was made based on the fact that 2D and 2.5D GIS solutions cannot analyse flood complex problems inside the urban area. Hence, the study sought to reduce time and effort for the decision-makers by proposing a 3D city model for flood risk management. The study used geospatial tools and databases such as ArcGIS, Watershed Modelling System (WMS), FME, PostgreSQL-PostGIS, and 3D City Database (3DCityDB) to generate the 3D model and to test the capability of establishing a unified geospatial data structure including the 3D city objects, hydrological data, and geological data. The findings showed the importance of addressing flood risks data and arranging it in the 3D geodatabase. It was also revealed that establishing a 3D city model based on the CityGML standard requires homogenised definitions and standards for city objects (surface and subsurface) as well as hydrological data.  

Supporting Institution

Higher Education, Research, and Innovation (MoHERI) of the Sultanate of Oman

References

  • Abdul Rahman, A., Rashidan, H., Musliman, I.A., Buyuksalih, G., Bayburt, S., Baskaraca, P., 2019. 3D Geospatial Database Schema for Istanbul 3D City Model. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W16, 11–16. https://doi.org/10.5194/isprs-archives-XLII-4-W16-11-2019
  • Al Kalbani, K., Abdul Rahman, A., 2019. Integration Between Surface and Subsurface Spatial Objects for Developing Oman 3D SDI Based on the CityGML Standard. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W16, 79–84. https://doi.org/10.5194/isprs-archives-XLII-4-W16-79-2019
  • Al Kalbani, K., Abdul Rahman, A., Al Awadhi, T., Alshannaq, F., 2018. Development Of A Framework for Implementing 3D Spatial Data Infrastructure In Oman – Issues And Challenges. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W9, 243–246. https://doi.org/10.5194/isprs-archives-XLII-4-W9-243-2018
  • Al-Kalbani, K., 2011. Monitoring and Assessing Flood Risks & Maintaining the Procedures to Limit their Danger using Geographical Information Systems, Remote Sensing and Hydrological Modeling (Case Study :Al-Seeb Willayat) ". Sultan Qaboos University.
  • Arroyo Ohori, K., Biljecki, F., Kumar, K., Ledoux, H., Stoter, J., 2018. Modeling Cities and Landscapes in 3D with CityGML, in: Building Information Modeling. Springer International Publishing, Cham, pp. 199–215. https://doi.org/10.1007/978-3-319-92862-3_11
  • Bakuła, K., StĘpnik, M., Kurczyński, Z., 2016. Influence of Elevation Data Source on 2D Hydraulic Modelling. Acta Geophys. 64, 1176–1192. https://doi.org/10.1515/acgeo-2016-0030
  • Bee, M., Benedetti, R., Espa, G., 2008. Spatial Models for Flood Risk Assessment. Environmetrics 19, 725–741. https://doi.org/10.1002/env.932
  • Biljecki, F., 2017. Level of Details in 3D City Models,Published PhD Thesis. Delft University of Technology. https://doi.org/10.4233/uuid:f12931b7-5113-47ef-bfd4-688aae3be248 Uzbekistan (Hz. Osman’s Mushafi). International Congress on Cultural Heritage and Tourism (ICCHT), 115-123, Bishkek, Kyrgzstan.
  • Biljecki, F., Ledoux, H., Stoter, J., 2017. Generating 3D City Models Without Elevation Data. Comput. Environ. Urban Syst. 64, 1–18. https://doi.org/10.1016/j.compenvurbsys.2017.01.001
  • Biljecki, F., Ledoux, H., Stoter, J., 2015a. Improving the Consistency of Multi-LoD CityGML Datasets by Removing Redundancy. pp. 1–17. https://doi.org/10.1007/978-3-319-12181-9_1
  • Biljecki, F., Stoter, J., Ledoux, H., Zlatanova, S., Çöltekin, A., 2015b. Applications of 3D City Models: State of the Art Review. ISPRS Int. J. Geo-Information 4, 2842–2889. https://doi.org/10.3390/ijgi4042842
  • Das, A., Chandel, K., Narain, A., 2017. Value of Geospatial Technology in Boosting Omans Economy, in: Oman Geospatial Forum 2017. Oman National Survey Authority, Muscat, pp. 1–74.
  • Dube, A., Ashrit, R., Kumar, S., Mamgain, A., 2020. Improvements in Tropical Cyclone Forecasting through Ensemble Prediction System at NCMRWF in India. Trop. Cyclone Res. Rev. https://doi.org/10.1016/j.tcrr.2020.04.003
  • Kensek, K.M., 2014. Building Information Modeling. Build. Inf. Model. 1–285. https://doi.org/10.4324/9781315797076
  • Kumar, K., Ledoux, H., Stoter, J., 2018. Dynamic 3D Visualisation of Floods: Case of the Netherlands. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W10, 83–87. https://doi.org/10.5194/isprs-archives-XLII-4-W10-83-2018
  • Li, J., Wong, D.W.S., 2010. Effects of DEM Sources on Hydrologic Applications. Comput. Environ. Urban Syst. 34, 251–261. https://doi.org/10.1016/j.compenvurbsys.2009.11.002
  • Mrmwroman, 2020. Precipitation Report from 27 May to 1 June, Mrmwroman Report.
  • Muhadi, N.A., Abdullah, A.F., Bejo, S.K., Mahadi, M.R., Mijic, A., 2020. The Use of LiDAR-Derived DEM in Flood Applications: A Review. Remote Sens. 12, 2308. https://doi.org/10.3390/rs12142308
  • NCSI, 2020. Monthly Statistical Bulletin, December 2020, Monthly Statistical Bulletin. https://doi.org/10.36548/jsws.2020.2
  • NCSI, 2017a. Oman National Spatial Data Infrastructure Strategy V5.0. National Center for Statistics and Information, Oman.
  • NCSI, 2017b. Oman National Spatial Data Infrastructure, 1st ed. National Center for Statistics and Information, Oman.
  • Preka, D., Doulamis, A., 2016. 3D Building Modeling in LoD2 Using the CityGML Standard. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-2/W2, 11–16. https://doi.org/10.5194/isprs-archives-XLII-2-W2-11-2016
  • Ruíz, A.A.B., 2015. An Urban Flooding Simulation Technique by Using 3D City Information Model 3, 54–67.
  • Siew, C., Kumar, P., 2019. CitySAC: A Query-Able CityGML Compression System. Smart Cities 2, 106–117. https://doi.org/10.3390/smartcities2010008
  • Soon, K.H., Tan, D., Khoo, V., Soon, K.H., Tan, D., Khoo, V., 2016. Initial Design to Develop a Cadastral System that Supports Digital Cadastre, 3D and Provenance for Singapore, in: 5th International Workshop on 3D Cadastres. pp. 419–432.
  • Stoter, J., Brink, L. Van Den, Vosselman, G., Goos, J., Verbree, E., Klooster, R., Berlo, L. Van, Vestjens, G., Reuvers, M., Thorn, S., 2010. A Generic Approach for 3D SDI in the Netherlands. Lect. Notes Comput. Sci. 1–22.
  • Stoter, J., Ploeger, H., Roes, R., Riet, E. Van Der, Biljecki, F., Stoter, J., Ploeger, H., Roes, R., Riet, E. Van Der, Biljecki, F., 2016. First 3D Cadastral Registration of Multi-level Ownerships Rights in the Netherlands, in: 5th International Workshop on 3D Cadastres. pp. 491–504.
  • Stoter, J., Vosselman, G., Dahmen, C., Oude Elberink, S., Ledoux, H., 2014. CityGML Implementation Specifications for a Countrywide 3D Data Set. Photogramm. Eng. Remote Sens. 80, 1069–1077. https://doi.org/10.14358/pers.80.11.1069
  • Stouffs, R., Tauscher, H., Biljecki, F., 2018. Achieving Complete and Near-Lossless Conversion from IFC to CityGML. ISPRS Int. J. Geo-Information 7, 355. https://doi.org/10.3390/ijgi7090355
  • Tymkow, P., Karpina, M., Borkowski, A., 2016. 3D GIS for Flood Modelling in River Valleys. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLI-B8, 175–178. https://doi.org/10.5194/isprsarchives-XLI-B8-175-2016
  • UNDP, 2004. Bureau for Crisis Prevention and Recovery ( Bcpr ) 2004 Report : Thematic Trust Fund for Crisis Prevention and Recovery United Nations Development Programme. Bur. Cris. Prev. Recover.
  • Yao, Z., Nagel, C., Kunde, F., Hudra, G., Willkomm, P., Donaubauer, A., Adolphi, T., Kolbe, T.H., 2018. 3DCityDB - a 3D Geodatabase Solution for the Management, Analysis, and Visualization of Semantic 3D City Models Based on CityGML. Open Geospatial Data, Softw. Stand. 3. https://doi.org/10.1186/s40965-018-0046-7
  • Zerboni, A., Perego, A., Mariani, G.S., Brandolini, F., Al Kindi, M., Regattieri, E., Zanchetta, G., Borgi, F., Charpentier, V., Cremaschi, M., 2020. Geomorphology of the Gebel Qara and Coastal Plain of Salalah (Dhofar, Southern Sultanate of Oman). J. Maps 16, 187–198. https://doi.org/10.1080/17445647.2019.1708488
  • Zlatanova, S., Ghawana, T., Kaur, A., Neuvel, J.M.M., 2014. Integrated Flood Disaster Management and Spatial Information: Case Studies of Netherlands and India. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XL–8, 147–154. https://doi.org/10.5194/isprsarchives-XL-8-147-2014
Year 2022, Volume: 7 Issue: 1, 17 - 23, 15.02.2022
https://doi.org/10.26833/ijeg.857971

Abstract

References

  • Abdul Rahman, A., Rashidan, H., Musliman, I.A., Buyuksalih, G., Bayburt, S., Baskaraca, P., 2019. 3D Geospatial Database Schema for Istanbul 3D City Model. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W16, 11–16. https://doi.org/10.5194/isprs-archives-XLII-4-W16-11-2019
  • Al Kalbani, K., Abdul Rahman, A., 2019. Integration Between Surface and Subsurface Spatial Objects for Developing Oman 3D SDI Based on the CityGML Standard. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W16, 79–84. https://doi.org/10.5194/isprs-archives-XLII-4-W16-79-2019
  • Al Kalbani, K., Abdul Rahman, A., Al Awadhi, T., Alshannaq, F., 2018. Development Of A Framework for Implementing 3D Spatial Data Infrastructure In Oman – Issues And Challenges. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W9, 243–246. https://doi.org/10.5194/isprs-archives-XLII-4-W9-243-2018
  • Al-Kalbani, K., 2011. Monitoring and Assessing Flood Risks & Maintaining the Procedures to Limit their Danger using Geographical Information Systems, Remote Sensing and Hydrological Modeling (Case Study :Al-Seeb Willayat) ". Sultan Qaboos University.
  • Arroyo Ohori, K., Biljecki, F., Kumar, K., Ledoux, H., Stoter, J., 2018. Modeling Cities and Landscapes in 3D with CityGML, in: Building Information Modeling. Springer International Publishing, Cham, pp. 199–215. https://doi.org/10.1007/978-3-319-92862-3_11
  • Bakuła, K., StĘpnik, M., Kurczyński, Z., 2016. Influence of Elevation Data Source on 2D Hydraulic Modelling. Acta Geophys. 64, 1176–1192. https://doi.org/10.1515/acgeo-2016-0030
  • Bee, M., Benedetti, R., Espa, G., 2008. Spatial Models for Flood Risk Assessment. Environmetrics 19, 725–741. https://doi.org/10.1002/env.932
  • Biljecki, F., 2017. Level of Details in 3D City Models,Published PhD Thesis. Delft University of Technology. https://doi.org/10.4233/uuid:f12931b7-5113-47ef-bfd4-688aae3be248 Uzbekistan (Hz. Osman’s Mushafi). International Congress on Cultural Heritage and Tourism (ICCHT), 115-123, Bishkek, Kyrgzstan.
  • Biljecki, F., Ledoux, H., Stoter, J., 2017. Generating 3D City Models Without Elevation Data. Comput. Environ. Urban Syst. 64, 1–18. https://doi.org/10.1016/j.compenvurbsys.2017.01.001
  • Biljecki, F., Ledoux, H., Stoter, J., 2015a. Improving the Consistency of Multi-LoD CityGML Datasets by Removing Redundancy. pp. 1–17. https://doi.org/10.1007/978-3-319-12181-9_1
  • Biljecki, F., Stoter, J., Ledoux, H., Zlatanova, S., Çöltekin, A., 2015b. Applications of 3D City Models: State of the Art Review. ISPRS Int. J. Geo-Information 4, 2842–2889. https://doi.org/10.3390/ijgi4042842
  • Das, A., Chandel, K., Narain, A., 2017. Value of Geospatial Technology in Boosting Omans Economy, in: Oman Geospatial Forum 2017. Oman National Survey Authority, Muscat, pp. 1–74.
  • Dube, A., Ashrit, R., Kumar, S., Mamgain, A., 2020. Improvements in Tropical Cyclone Forecasting through Ensemble Prediction System at NCMRWF in India. Trop. Cyclone Res. Rev. https://doi.org/10.1016/j.tcrr.2020.04.003
  • Kensek, K.M., 2014. Building Information Modeling. Build. Inf. Model. 1–285. https://doi.org/10.4324/9781315797076
  • Kumar, K., Ledoux, H., Stoter, J., 2018. Dynamic 3D Visualisation of Floods: Case of the Netherlands. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-4/W10, 83–87. https://doi.org/10.5194/isprs-archives-XLII-4-W10-83-2018
  • Li, J., Wong, D.W.S., 2010. Effects of DEM Sources on Hydrologic Applications. Comput. Environ. Urban Syst. 34, 251–261. https://doi.org/10.1016/j.compenvurbsys.2009.11.002
  • Mrmwroman, 2020. Precipitation Report from 27 May to 1 June, Mrmwroman Report.
  • Muhadi, N.A., Abdullah, A.F., Bejo, S.K., Mahadi, M.R., Mijic, A., 2020. The Use of LiDAR-Derived DEM in Flood Applications: A Review. Remote Sens. 12, 2308. https://doi.org/10.3390/rs12142308
  • NCSI, 2020. Monthly Statistical Bulletin, December 2020, Monthly Statistical Bulletin. https://doi.org/10.36548/jsws.2020.2
  • NCSI, 2017a. Oman National Spatial Data Infrastructure Strategy V5.0. National Center for Statistics and Information, Oman.
  • NCSI, 2017b. Oman National Spatial Data Infrastructure, 1st ed. National Center for Statistics and Information, Oman.
  • Preka, D., Doulamis, A., 2016. 3D Building Modeling in LoD2 Using the CityGML Standard. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLII-2/W2, 11–16. https://doi.org/10.5194/isprs-archives-XLII-2-W2-11-2016
  • Ruíz, A.A.B., 2015. An Urban Flooding Simulation Technique by Using 3D City Information Model 3, 54–67.
  • Siew, C., Kumar, P., 2019. CitySAC: A Query-Able CityGML Compression System. Smart Cities 2, 106–117. https://doi.org/10.3390/smartcities2010008
  • Soon, K.H., Tan, D., Khoo, V., Soon, K.H., Tan, D., Khoo, V., 2016. Initial Design to Develop a Cadastral System that Supports Digital Cadastre, 3D and Provenance for Singapore, in: 5th International Workshop on 3D Cadastres. pp. 419–432.
  • Stoter, J., Brink, L. Van Den, Vosselman, G., Goos, J., Verbree, E., Klooster, R., Berlo, L. Van, Vestjens, G., Reuvers, M., Thorn, S., 2010. A Generic Approach for 3D SDI in the Netherlands. Lect. Notes Comput. Sci. 1–22.
  • Stoter, J., Ploeger, H., Roes, R., Riet, E. Van Der, Biljecki, F., Stoter, J., Ploeger, H., Roes, R., Riet, E. Van Der, Biljecki, F., 2016. First 3D Cadastral Registration of Multi-level Ownerships Rights in the Netherlands, in: 5th International Workshop on 3D Cadastres. pp. 491–504.
  • Stoter, J., Vosselman, G., Dahmen, C., Oude Elberink, S., Ledoux, H., 2014. CityGML Implementation Specifications for a Countrywide 3D Data Set. Photogramm. Eng. Remote Sens. 80, 1069–1077. https://doi.org/10.14358/pers.80.11.1069
  • Stouffs, R., Tauscher, H., Biljecki, F., 2018. Achieving Complete and Near-Lossless Conversion from IFC to CityGML. ISPRS Int. J. Geo-Information 7, 355. https://doi.org/10.3390/ijgi7090355
  • Tymkow, P., Karpina, M., Borkowski, A., 2016. 3D GIS for Flood Modelling in River Valleys. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XLI-B8, 175–178. https://doi.org/10.5194/isprsarchives-XLI-B8-175-2016
  • UNDP, 2004. Bureau for Crisis Prevention and Recovery ( Bcpr ) 2004 Report : Thematic Trust Fund for Crisis Prevention and Recovery United Nations Development Programme. Bur. Cris. Prev. Recover.
  • Yao, Z., Nagel, C., Kunde, F., Hudra, G., Willkomm, P., Donaubauer, A., Adolphi, T., Kolbe, T.H., 2018. 3DCityDB - a 3D Geodatabase Solution for the Management, Analysis, and Visualization of Semantic 3D City Models Based on CityGML. Open Geospatial Data, Softw. Stand. 3. https://doi.org/10.1186/s40965-018-0046-7
  • Zerboni, A., Perego, A., Mariani, G.S., Brandolini, F., Al Kindi, M., Regattieri, E., Zanchetta, G., Borgi, F., Charpentier, V., Cremaschi, M., 2020. Geomorphology of the Gebel Qara and Coastal Plain of Salalah (Dhofar, Southern Sultanate of Oman). J. Maps 16, 187–198. https://doi.org/10.1080/17445647.2019.1708488
  • Zlatanova, S., Ghawana, T., Kaur, A., Neuvel, J.M.M., 2014. Integrated Flood Disaster Management and Spatial Information: Case Studies of Netherlands and India. ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. XL–8, 147–154. https://doi.org/10.5194/isprsarchives-XL-8-147-2014
There are 34 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Khalid Al Kalbani 0000-0002-3268-6831

Alias Abdul Rahman This is me

Publication Date February 15, 2022
Published in Issue Year 2022 Volume: 7 Issue: 1

Cite

APA Al Kalbani, K., & Rahman, A. A. (2022). 3D city model for monitoring flash flood risks in Salalah, Oman. International Journal of Engineering and Geosciences, 7(1), 17-23. https://doi.org/10.26833/ijeg.857971
AMA Al Kalbani K, Rahman AA. 3D city model for monitoring flash flood risks in Salalah, Oman. IJEG. February 2022;7(1):17-23. doi:10.26833/ijeg.857971
Chicago Al Kalbani, Khalid, and Alias Abdul Rahman. “3D City Model for Monitoring Flash Flood Risks in Salalah, Oman”. International Journal of Engineering and Geosciences 7, no. 1 (February 2022): 17-23. https://doi.org/10.26833/ijeg.857971.
EndNote Al Kalbani K, Rahman AA (February 1, 2022) 3D city model for monitoring flash flood risks in Salalah, Oman. International Journal of Engineering and Geosciences 7 1 17–23.
IEEE K. Al Kalbani and A. A. Rahman, “3D city model for monitoring flash flood risks in Salalah, Oman”, IJEG, vol. 7, no. 1, pp. 17–23, 2022, doi: 10.26833/ijeg.857971.
ISNAD Al Kalbani, Khalid - Rahman, Alias Abdul. “3D City Model for Monitoring Flash Flood Risks in Salalah, Oman”. International Journal of Engineering and Geosciences 7/1 (February 2022), 17-23. https://doi.org/10.26833/ijeg.857971.
JAMA Al Kalbani K, Rahman AA. 3D city model for monitoring flash flood risks in Salalah, Oman. IJEG. 2022;7:17–23.
MLA Al Kalbani, Khalid and Alias Abdul Rahman. “3D City Model for Monitoring Flash Flood Risks in Salalah, Oman”. International Journal of Engineering and Geosciences, vol. 7, no. 1, 2022, pp. 17-23, doi:10.26833/ijeg.857971.
Vancouver Al Kalbani K, Rahman AA. 3D city model for monitoring flash flood risks in Salalah, Oman. IJEG. 2022;7(1):17-23.

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