IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i3p575-d1082460.html
   My bibliography  Save this article

A Geo-Hazard Risk Assessment Technique for Analyzing Impacts of Surface Subsidence within Onyeama Mine, South East Nigeria

Author

Listed:
  • Nixon N. Nduji

    (Centre for Environmental Management and Control (CEMAC), University of Nigeria (UNN), Enugu 410001, Nigeria
    Department of Surveying and Geoinformatics, Enugu State University of Science and Technology (ESUT), PMB 01660, Enugu 402004, Nigeria)

  • Christian N. Madu

    (Centre for Environmental Management and Control (CEMAC), University of Nigeria (UNN), Enugu 410001, Nigeria
    Department of Management and Management Science, Lubin School of Business, Pace University, 1 Pace Plaza, New York, NY 10038, USA)

  • Chukwuebuka C. Okafor

    (Centre for Environmental Management and Control (CEMAC), University of Nigeria (UNN), Enugu 410001, Nigeria)

  • Martins U. Ezeoha

    (Centre for Environmental Management and Control (CEMAC), University of Nigeria (UNN), Enugu 410001, Nigeria)

Abstract

This paper proposes a geo-hazard risk assessment technique to analyze the impacts of surface subsidence monitored in a major coal mine in Nigeria. In many developing countries, disaster risk management schemes have mainly focused on traditional singular hazard assessment, vulnerability assessment, or risk assessment. However, it is difficult to use a singular application to adequately address hazard assessment due to the variation in data requirements, factors associated with the hazards, and the various elements at risk. Most times, hazard assessment schemes heavily rely on data and techniques from different global organizations that collate data on disasters, using various scales and objectives to make informed decisions. Several challenges seemingly arise from total reliance on these kinds of data due to standardization, the exact number of potential victims, and the purpose of the data collection. This makes disaster information collected at the local level unique and assessment schemes more complete; however, the coverage is limited worldwide. The proposed approach combines the spatial relationship between vulnerability assessment and elements at risk to highlight the grave consequences of potential disasters. Thus, the aim is to underscore the importance of integrating local-level inputs in analyzing risk factors and vulnerability indicators for hazard assessment. This study was conducted at the Onyeama coal mine in South East Nigeria. This area has experienced severe negative impacts of subsidence over the years. We exploit data from Sentinel-1 Synthetic Aperture Radar (SAR) Satellites and Small-Baseline Subset Differential Interferometric Synthetic Aperture Radar (SBAS-DInSAR) technique to map the study area. The results generate an elements-at-risk database with a particular focus on population density, road networks, and building networks identified as indices for loss estimation.

Suggested Citation

  • Nixon N. Nduji & Christian N. Madu & Chukwuebuka C. Okafor & Martins U. Ezeoha, 2023. "A Geo-Hazard Risk Assessment Technique for Analyzing Impacts of Surface Subsidence within Onyeama Mine, South East Nigeria," Land, MDPI, vol. 12(3), pages 1-21, February.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:575-:d:1082460
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/3/575/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/12/3/575/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Omid Ghorbanzadeh & Hashem Rostamzadeh & Thomas Blaschke & Khalil Gholaminia & Jagannath Aryal, 2018. "A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(2), pages 497-517, November.
    2. Eric Tate, 2012. "Social vulnerability indices: a comparative assessment using uncertainty and sensitivity analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 63(2), pages 325-347, September.
    3. Sullivan-Wiley, Kira A. & Short Gianotti, Anne G., 2017. "Risk Perception in a Multi-Hazard Environment," World Development, Elsevier, vol. 97(C), pages 138-152.
    4. Muhammad Wafiy Adli Ramli & Nor Eliza Alias & Halimah Mohd Yusof & Zulkifli Yusop & Shazwin Mat Taib, 2021. "Development of a Local, Integrated Disaster Risk Assessment Framework for Malaysia," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    5. Neiler Medina & Yared Abayneh Abebe & Arlex Sanchez & Zoran Vojinovic, 2020. "Assessing Socioeconomic Vulnerability after a Hurricane: A Combined Use of an Index-Based approach and Principal Components Analysis," Sustainability, MDPI, vol. 12(4), pages 1-31, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhammad Wafiy Adli Ramli & Nor Eliza Alias & Halimah Mohd Yusof & Zulkifli Yusop & Shazwin Mat Taib, 2021. "Development of a Local, Integrated Disaster Risk Assessment Framework for Malaysia," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    2. Bolaños-Valencia, Ingrid & Villegas-Palacio, Clara & López-Gómez, Connie Paola & Berrouet, Lina & Ruiz, Aura, 2019. "Social perception of risk in socio-ecological systems. A qualitative and quantitative analysis," Ecosystem Services, Elsevier, vol. 38(C), pages 1-1.
    3. Gainbi Park & Zengwang Xu, 2022. "The constituent components and local indicator variables of social vulnerability index," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(1), pages 95-120, January.
    4. Wei Zhang & Qianxing Zhao & Minjie Pei, 2021. "How much uncertainty does the choice of data transforming method brings to heat risk mapping? Evidence from China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 349-373, March.
    5. Mohsen Alizadeh & Esmaeil Alizadeh & Sara Asadollahpour Kotenaee & Himan Shahabi & Amin Beiranvand Pour & Mahdi Panahi & Baharin Bin Ahmad & Lee Saro, 2018. "Social Vulnerability Assessment Using Artificial Neural Network (ANN) Model for Earthquake Hazard in Tabriz City, Iran," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    6. Jonathan W. F. Remo & Nicholas Pinter & Moe Mahgoub, 2016. "Assessing Illinois’s flood vulnerability using Hazus-MH," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 265-287, March.
    7. Majid Mohammady & Hamid Reza Pourghasemi & Mojtaba Amiri, 2019. "Assessment of land subsidence susceptibility in Semnan plain (Iran): a comparison of support vector machine and weights of evidence data mining algorithms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(2), pages 951-971, November.
    8. Paulus, David & Meesters, Kenny & Vries, Gerdien de & Walle, Bartel Van de, 2019. "The reciprocity of data integration in disaster risk analysis," Other publications TiSEM 5e5a778f-bda8-4612-b780-b, Tilburg University, School of Economics and Management.
    9. Fei Li & Tan Yigitcanlar & Madhav Nepal & Kien Nguyen Thanh & Fatih Dur, 2022. "Understanding Urban Heat Vulnerability Assessment Methods: A PRISMA Review," Energies, MDPI, vol. 15(19), pages 1-34, September.
    10. Mohammad Abdul Quader & Amanat Ullah Khan & Matthieu Kervyn, 2017. "Assessing Risks from Cyclones for Human Lives and Livelihoods in the Coastal Region of Bangladesh," IJERPH, MDPI, vol. 14(8), pages 1-26, July.
    11. Richard R. Shaker & Joseph Aversa & Victoria Papp & Bryant M. Serre & Brian R. Mackay, 2020. "Showcasing Relationships between Neighborhood Design and Wellbeing Toronto Indicators," Sustainability, MDPI, vol. 12(3), pages 1-24, January.
    12. Nikole Guerrero & Marta Contreras & Alondra Chamorro & Carolina Martínez & Tomás Echaveguren, 2023. "Social vulnerability in Chile: challenges for multi-scale analysis and disaster risk reduction," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 3067-3102, July.
    13. Viviana Maura Santos & Cláudio Henrique Santos Grecco & Ricardo José Matos Carvalho & Paulo Victor Rodrigues Carvalho, 2020. "A fuzzy model to assess the resilience of Protection and Civil Defense Organizations," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(3), pages 735-759, June.
    14. Sukanta Malakar & Abhishek K. Rai & Arun K. Gupta, 2023. "Earthquake risk mapping in the Himalayas by integrated analytical hierarchy process, entropy with neural network," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 951-975, March.
    15. Novak, D.C. & Sullivan, J.F. & Sentoff, K. & Dowds, J., 2020. "A framework to guide strategic disinvestment in roadway infrastructure considering social vulnerability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 436-451.
    16. Brown, Philip & Daigneault, Adam J. & Tjernström, Emilia & Zou, Wenbo, 2018. "Natural disasters, social protection, and risk perceptions," World Development, Elsevier, vol. 104(C), pages 310-325.
    17. Hasibuan, Abdul Muis & Gregg, Daniel & Stringer, Randy, 2020. "Accounting for diverse risk attitudes in measures of risk perceptions: A case study of climate change risk for small-scale citrus farmers in Indonesia," Land Use Policy, Elsevier, vol. 95(C).
    18. Ruikun Peng & Yinyin Zhao & Ehsan Elahi & Benhong Peng, 2021. "Does disaster shocks affect farmers’ willingness for insurance? Mediating effect of risk perception and survey data from risk-prone areas in East China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 2883-2899, April.
    19. Zachary T. Goodman & Caitlin A. Stamatis & Justin Stoler & Christopher T. Emrich & Maria M. Llabre, 2021. "Methodological challenges to confirmatory latent variable models of social vulnerability," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 2731-2749, April.
    20. Ibolya Török, 2018. "Qualitative Assessment of Social Vulnerability to Flood Hazards in Romania," Sustainability, MDPI, vol. 10(10), pages 1-20, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:12:y:2023:i:3:p:575-:d:1082460. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.