Geomatics and Environmental Engineering, vol. 18, no. 3

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Vol. 18 No. 3 (2024): Geomatics and Environmental Engineering

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Submitted
Nov 27, 2023
Accepted
Apr 12, 2024
Published
May 15, 2024
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This work is licensed under a Creative Commons Attribution 4.0 International License.

Geomatics-enabled Interdisciplinary Approach Based on Geospatial Data Processing for Hydrogeological Risk-analysis

https://doi.org/10.7494/geom.2024.18.3.63
Francesco Di Stefano
Università Politecnica delle Marche, Facoltà di Ingegneria, Ancona, Italy
https://orcid.org/0000-0002-0604-7163
Stefano Chiappini
Università Politecnica delle Marche, Facoltà di Ingegneria, Ancona, Italy
https://orcid.org/0000-0001-8776-2232
Marsia Sanità
Università Politecnica delle Marche, Facoltà di Ingegneria, Ancona, Italy
https://orcid.org/0009-0002-9828-2626
Roberto Pierdicca
Università Politecnica delle Marche, Facoltà di Ingegneria, Ancona, Italy
https://orcid.org/0000-0002-9160-834X
Eva Savina Malinverni
Università Politecnica delle Marche, Facoltà di Ingegneria, Ancona, Italy
https://orcid.org/0000-0001-6582-2943

Corresponding Author(s) : Francesco Di Stefano

f.distefano@staff.univpm.it

Geomatics and Environmental Engineering, Vol. 18 No. 3 (2024): Geomatics and Environmental Engineering

Abstract

Hydrogeological risks that are associated with rivers have emerged as a significant concern worldwide, impacting both natural ecosystems and human settlements. This contribution presents an interdisciplinary project that leverages many technologies for data-acquisition and modeling to comprehensively analyze and manage risks in riverine environments. The project integrates geomatics, geological, and hydrological techniques to provide a holistic understanding of river dynamics and their associated hazards. As a central component of this project, geomatics plays a pivotal role in instrumental field surveying through the deployment of photogrammetry and LiDAR instruments. Remote-sensing data from satellite imagery further enriches the project’s temporal analysis capabilities. By analyzing this data over time, researchers can monitor changes in river patterns, land use, and climate-related variables; this helps identify trends and potential triggers for hydrological events. To manage and integrate the vast amount of geospatial information that is generated, a geodatabase within a geographic information system (GIS) has been established. It enables efficient data storage, retrieval, and analysis, fostering collaboration among multidisciplinary researcher teams. This system offers tools for risk-assessment, modeling, and scenario planning; these allow for proactive measures for mitigating hydrological risks.

Keywords

geomatics remote sensing geoinformation geodatabase hydrogeological risk
Di Stefano, F., Chiappini, S., Sanità, M., Pierdicca, R., & Malinverni, E. S. (2024). Geomatics-enabled Interdisciplinary Approach Based on Geospatial Data Processing for Hydrogeological Risk-analysis. Geomatics and Environmental Engineering, 18(3), 63–80. https://doi.org/10.7494/geom.2024.18.3.63
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References
  1. Gattinoni P., Scesi L., Arieni L., Zaffroni F.: A new rating system for hydrogeological risk management along railway infrastructures in Prealpine zone (northern Italy). Innovative Infrastructure Solutions, vol. 6(2), 2021, 120. https://doi.org/10.1007/s41062-021-00488-y.
  2. Merisalu J., Sundell J., Rosén L.: A framework for risk-based cost-benefit analysis for decision support on hydrogeological risks in underground construction. Geosciences, vol. 11(2), 2021, 82. https://doi.org/10.3390/geosciences11020082.
  3. Italian Institute for Environmental Protection and Research (ISPRA): Report on flood hazard conditions in Italy and associated risk indicators. ISPRA Reports 353/2021, https://www.isprambiente.gov.it/en/publications/reports/report-on-flood-hazard-conditions-in-italy-and-associated-risk-indicators [access: 17.10.2023].
  4. Italian Institute for Environmental Protection and Research (ISPRA): Landslides and floods in Italy: Hazard and risk indicators – 2021 Edition. ISPRA Reports 356/2021. https://www.isprambiente.gov.it/en/publications/reports/landslides-and-floods-in-italy-hazard-and-risk-indicators-2021-edition [access: 17.10.2023].
  5. Costabile P., Costanzo C., De Lorenzo G., De Santis R., Penna N., Macchione F.: Terrestrial and airborne laser scanning and 2-D modelling for 3-D flood hazard maps in urban areas: New opportunities and perspectives. Environmental Modelling & Software, vol. 135, 2021, 104889. https://doi.org/10.1016/j.envsoft.2020.104889.
  6. Hariyono M.I., Kurniawan A.A., Tambunan M.P.: The use of airborne Lidar data to analyze flood disaster area: case study of Sekarbela Subdistrict, Mataram. IOP Conference Series: Earth and Environmental Science, vol. 950(1), 2022, 012086. https://doi.org/10.1088/1755-1315/950/1/012086.
  7. Saputra A., Sigit A.A., Priyana Y., Abror A.M., Lia Sari A.N., Nursetiyani O.: A low-cost drone mapping and simple participatory GIS to support the urban flood modelling. Geographia Technica, vol. 17(2), 2022, pp. 35–46. https://doi.org/10.21163/GT_2022.172.04.
  8. Di Stefano F., Chiappini S., Gorreja A., Balestra M., Pierdicca R.: Mobile 3D scan LiDAR: A literature review. Geomatics, Natural Hazards and Risk, vol. 12(1), 2021, pp. 2387–2429. https://doi.org/10.1080/19475705.2021.1964617.
  9. Ammirati L., Chirico R., Di Martire D., Mondillo N.: Application of multispectral remote sensing for mapping flood-affected zones in the Brumadinho mining district (Minas Gerais, Brasil). Remote Sensing, vol. 14(6), 2022, 1501. https://doi.org/10.3390/rs14061501.
  10. Abdelkarim A., Awawdeh M.M., Alogayell H.M., Al-Alola S.S.: Integration of remote sensing and hydrologic, hydraulic modelling on assessment flood risk and mitigation: Al-Lith city, KSA. GEOMATE Journal, vol. 18(70), 2020, pp. 252–280. https://geomatejournal.com/geomate/article/view/647.
  11. Zingaro M., La Salandra M., Capolongo D.: New perspectives of earth surface remote detection for hydro-geomorphological monitoring of rivers. Sustainability, vol. 14(21), 2022, 14093. https://doi.org/10.3390/su142114093.
  12. Samela C., Coluzzi R., Imbrenda V., Manfreda S., Lanfredi M.: Satellite flood detection integrating hydrogeomorphic and spectral indices. GIScience & Remote Sensing, vol. 59(1), 2022, pp. 1997–2018. https://doi.org/10.1080/15481603.2022.2143670.
  13. Tariq A., Yan J., Ghaffar B., Qin S., Mousa B.G., Shari i A., Huq M.E., Aslam M.: Flash flood susceptibility assessment and zonation by integrating analytic hierarchy process and frequency ratio model with diverse spatial data. Water, vol. 14(19), 2022, 3069. https://doi.org/10.3390/w14193069.
  14. Xue F., Gao W., Yin C., Chen X., Xia Z., Lv Y., Zhou Y., Wang M.: Flood monitoring by integrating normalized difference flood index and probability distribution of water bodies. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, 2022, pp. 4170–4179. https://doi.org/10.1109/JSTARS.2022.3176388.
  15. Phy S.R., Sok T., Try S., Chan R., Uk S., Hen C., Oeurng C.: Flood hazard and management in Cambodia: A review of activities, knowledge gaps, and research direction. Climate, vol. 10(11), 2022, 162. https://doi.org/10.3390/cli10110162.
  16. Solovey T.: Flooded wetlands mapping from Sentinel-2 imagery with spectral water index: a case study of Kampinos National Park in central Poland. Geological Quarterly, vol. 64(2), 2020, pp. 492–505. https://doi.org/10.7306/gq.1509.
  17. Atefi M.R., Miura H.: Detection of flash flood inundated areas using relative difference in NDVI from Sentinel-2 images: A case study of the August 2020 Event in Charikar, Afghanistan. Remote Sensing, vol. 14(15), 2022, 3647. https://doi.org/10.3390/rs14153647.
  18. Sidi Almouctar M.A., Wu Y., Kumar A., Zhao F., Mambu K.J., Sadek M.: Spatiotemporal analysis of vegetation cover changes around surface water based on NDVI: A case study in Korama basin, Southern Zinder, Niger. Applied Water Science, vol. 11(1), 2021, 4. https://doi.org/10.1007/s13201-020-01332-x.
  19. Morelli S., Segoni S., Manzo G., Ermini L., Catani F.: Urban planning, flood risk and public policy: The case of the Arno River, Firenze, Italy. Applied Geography, vol. 34, 2012, pp. 205–218. https://doi.org/10.1016/j.apgeog.2011.10.020.
  20. Giardino M., Perotti L., Lanfranco M., Perrone G.: GIS and geomatics for disaster management and emergency relief: A proactive response to natural hazards. Applied Geomatics, vol. 4(1), 2012, pp. 33–46. https://doi.org/10.1007/s12518-011-0071-z.
  21. Balabanova S., Koshinchanov G., Stoyanova V., Yordanova V.: Geodatabase for occurred floods to support preliminary flood risk assessment. [in:] 19th International Multidiciplinary Scientific Geoconference SGEM 2019, 30 June – 6 July 2019, Albena Bulgaria: Conference Proceedings, vol. 19(3.1), STEF92 Technology Limited, Sofia 2019, pp. 225–232.
  22. Tomar P., Singh S.K., Kanga S., Meraj G., Kranjčić N., Đurin B., Pattanaik A.: GIS-based urban flood risk assessment and management – a case study of Delhi National Capital Territory (NCT), India. Sustainability, vol. 13(22), 2021, 12850. https://doi.org/10.3390/su132212850.
  23. Rasn K.H., Nsaif Q.A., Al-Obaidi M.A., John Y.M.: Designation of flood risk zones using the geographic information system technique and remote sensing data in wasit, Iraq. Geomatics and Environmental Engineering, vol. 15(3), 2021, pp. 129–140. https://doi.org/10.7494/geom.2021.15.3.129.
  24. Zegait R., Şen Z., Pulido-Bosch A., Madi H., Hamadeha B.: Flash flood risk and climate analysis in the extreme south of Algeria (the case of In-Guezzam City). Geomatics and Environmental Engineering, vol. 16(4), 2022, pp. 157–185. https://doi.org/10.7494/geom.2022.16.4.157.
  25. Ismanto R. D., Fitriana H. L., Manalu J., Purboyo AA., Prasasti I.: Development of flood-hazard-mapping model using random forest and frequency ratio in Sumedang Regency, West Java, Indonesia. Geomatics and Environmental Engineering, vol. 17(6), 2023, pp. 157–185. https://doi.org/10.7494/geom.2022.16.4.157.
  26. Di Stefano F., Cabrelles M., García-Asenjo L., Lerma J.L., Malinverni E.S., Baselga S., Garrigues P., Pierdicca R.: Evaluation of long-range Mobile Mapping System (MMS) and close-range photogrammetry for deformation monitoring. A case study of Cortes de Pallás in Valencia (Spain). Applied Sciences, vol. 10(19), 2020, 6831. https://doi.org/10.3390/app10196831.
  27. Di Stefano F., Chiappini S., Piccinini F., Pierdicca R.: Integration and assessment between 3D data from different geomatics techniques. Case study: The ancient city walls of San Ginesio (Italy). [in:] Parente C., Troisi S., Vettore A. (eds.), R3 in Geomatics: Research, Results and Review: First International Workshop in memory of Prof. Raffaele Santamaria on R3 in Geomatics: Research, Results and Review, R3GEO 2019, Naples, Italy, October 10–11, 2019, Revised Selected Papers, Communications in Computer and Information Science, vol. 1246, Springer, Cham 2019, pp. 186–197. https://doi.org/10.1007/978-3-030-62800-0_15.
  28. Di Stefano F., Sanità M., Malinverni E.S., Doti G.: Geomatic technologies to valorize historical watermills. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLVIII-M-2-2023, 2023, pp. 511–518. https://doi.org/10.5194/isprs-archives-XLVIII-M-2-2023-511-2023.
  29. Piccinini F., Gorreja A., Di Stefano F., Pierdicca R., Sanchez Aparicio L.J., Malinverni E.S.: Preservation of villages in Central Italy: Geomatic techniques’ integration and GIS strategies for the post-earthquake assessment. ISPRS International Journal of Geo-Information, vol. 11(5), 2022, 291. https://doi.org/10.3390/ijgi11050291.
  30. Gorgoglione L., Malinverni E.S., Smaniotto Costa C., Pierdicca R., Di Stefano F.: Exploiting 2D/3D geomatics data for the management, promotion, and valorization of underground built heritage. Smart Cities, vol. 6(1), 2023, pp. 243–262. https://doi.org/10.3390/smartcities6010012.
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