IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i22p14782-d967910.html
   My bibliography  Save this article

Atmospheric Anomalies Associated with the 2021 M w 7.2 Haiti Earthquake Using Machine Learning from Multiple Satellites

Author

Listed:
  • Muhammad Muzamil Khan

    (GNSS and Space Education Research Laboratory, National Center of GIS and Space Applications, Department of Space Science, Institute of Space Technology, Islamabad 44000, Pakistan)

  • Bushra Ghaffar

    (Department of Environmental Science, Faculty of Basic and Applied Sciences, International Islamic University, Islamabad 44000, Pakistan)

  • Rasim Shahzad

    (GNSS and Space Education Research Laboratory, National Center of GIS and Space Applications, Department of Space Science, Institute of Space Technology, Islamabad 44000, Pakistan)

  • M. Riaz Khan

    (Department of Mathematics, Quaid-i-Azam University, Islamabad 44000, Pakistan)

  • Munawar Shah

    (GNSS and Space Education Research Laboratory, National Center of GIS and Space Applications, Department of Space Science, Institute of Space Technology, Islamabad 44000, Pakistan)

  • Ali H. Amin

    (Deanship of Scientific Research, Umm Al-Qura University, Makkah 24382, Saudi Arabia
    Zoology Department, Faculty of Science, Mansoura University, Mansoura 35516, Egypt)

  • Sayed M. Eldin

    (Center of Research, Faculty of Engineering, Future University in Egypt, New Cairo 11835, Egypt)

  • Najam Abbas Naqvi

    (GNSS and Space Education Research Laboratory, National Center of GIS and Space Applications, Department of Space Science, Institute of Space Technology, Islamabad 44000, Pakistan)

  • Rashid Ali

    (School of Mathematics and Statistics, Central South University, Changsha 410083, China)

Abstract

The remote sensing-based Earth satellites has become a beneficial instrument for the monitoring of natural hazards. This study includes a multi-sensors analysis to estimate the spatial-temporal variations of atmospheric parameters as precursory signals to the M w 7.2 Haiti Earthquake (EQ). We studied EQ anomalies in Land Surface Temperature (LST), Air Temperature (AT), Relative Humidity (RH), Air Pressure (AP), and Outgoing Longwave Radiation (OLR). Moreover, we found EQ-associated atmospheric abnormalities in a time window of 3–10 days before the main shock by different methods (e.g., statistical, wavelet transformation, deep learning, and Machine Learning (ML)-based neural networks). We observed a sharp decrease in the RH and AP before the main shock, followed by an immense enhancement in AT. Similarly, we also observed enhancement in LST and OLR around the seismic preparation region within 3–10 days before the EQ, which validates the precursory behavior of all the atmospheric parameters. These multiple-parameter irregularities can contribute with the physical understanding of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) in the future in order to forecast EQs.

Suggested Citation

  • Muhammad Muzamil Khan & Bushra Ghaffar & Rasim Shahzad & M. Riaz Khan & Munawar Shah & Ali H. Amin & Sayed M. Eldin & Najam Abbas Naqvi & Rashid Ali, 2022. "Atmospheric Anomalies Associated with the 2021 M w 7.2 Haiti Earthquake Using Machine Learning from Multiple Satellites," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14782-:d:967910
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/22/14782/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/22/14782/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhenhao Zhang & Changchun Luo & Zhenpeng Zhao, 2020. "Application of probabilistic method in maximum tsunami height prediction considering stochastic seabed topography," 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. 104(3), pages 2511-2530, December.
    2. Zhang, Xiaoying & Ma, Funing & Yin, Shangxian & Wallace, Corey D & Soltanian, Mohamad Reza & Dai, Zhenxue & Ritzi, Robert W. & Ma, Ziqi & Zhan, Chuanjun & Lü, Xiaoshu, 2021. "Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review," Applied Energy, Elsevier, vol. 303(C).
    3. Wei Xie & Wen Nie & Pooya Saffari & Luis F. Robledo & Pierre-Yves Descote & Wenbin Jian, 2021. "Landslide hazard assessment based on Bayesian optimization–support vector machine in Nanping City, 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. 109(1), pages 931-948, October.
    4. José Francisco de Oliveira-Júnior & Munawar Shah & Ayesha Abbas & Washington Luiz Félix Correia Filho & Carlos Antonio da Silva Junior & Dimas de Barros Santiago & Paulo Eduardo Teodoro & David Mendes, 2022. "Spatiotemporal Analysis of Fire Foci and Environmental Degradation in the Biomes of Northeastern Brazil," Sustainability, MDPI, vol. 14(11), pages 1-19, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohammad Reza Mansouri Daneshvar & Friedemann T. Freund & Majid Ebrahimi, 2023. "Spatial and Temporal Analysis of Climatic Precursors before Major Earthquakes in Iran (2011–2021)," Sustainability, MDPI, vol. 15(14), pages 1-30, July.

    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. Peijie Yang & Guangwei Wu & Sha Gu & Qin Guan & Lichun Wang, 2022. "The Effects of Pore Geometry on Late Time Solute Transport with the Presence of Recirculation Zone," Energies, MDPI, vol. 15(13), pages 1-9, June.
    2. Singh, Sudhir & Sakkaravarthi, K. & Murugesan, K., 2023. "Lump and soliton on certain spatially-varying backgrounds for an integrable (3+1) dimensional fifth-order nonlinear oceanic wave model," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    3. Wedad Albalawi & Rasool Shah & Nehad Ali Shah & Jae Dong Chung & Sherif M. E. Ismaeel & Samir A. El-Tantawy, 2023. "Analyzing Both Fractional Porous Media and Heat Transfer Equations via Some Novel Techniques," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    4. Ali Aldrees, 2021. "Water management in Saudi Arabia: a case study of Makkah Al Mukarramah region," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(9), pages 13650-13666, September.
    5. Chuhan Wang & Qigen Lin & Leibin Wang & Tong Jiang & Buda Su & Yanjun Wang & Sanjit Kumar Mondal & Jinlong Huang & Ying Wang, 2022. "The influences of the spatial extent selection for non-landslide samples on statistical-based landslide susceptibility modelling: a case study of Anhui Province in 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. 112(3), pages 1967-1988, July.
    6. Deborah Simon Mwakapesa & Yimin Mao & Xiaoji Lan & Yaser Ahangari Nanehkaran, 2023. "Landslide Susceptibility Mapping Using DIvisive ANAlysis (DIANA) and RObust Clustering Using linKs (ROCK) Algorithms, and Comparison of Their Performance," Sustainability, MDPI, vol. 15(5), pages 1-20, February.
    7. Tingting Cai & Dongmin Yu & Huanan Liu & Fengkai Gao, 2022. "RETRACTED: Computational Analysis of Variational Inequalities Using Mean Extra-Gradient Approach," Mathematics, MDPI, vol. 10(13), pages 1-14, July.
    8. Hazem Ghassan Abdo & Hussein Almohamad & Ahmed Abdullah Al Dughairi & Motirh Al-Mutiry, 2022. "GIS-Based Frequency Ratio and Analytic Hierarchy Process for Forest Fire Susceptibility Mapping in the Western Region of Syria," Sustainability, MDPI, vol. 14(8), pages 1-20, April.
    9. Xiaojie Geng & Shunchuan Wu & Yanjie Zhang & Junlong Sun & Haiyong Cheng & Zhongxin Zhang & Shijiang Pu, 2023. "Developing hybrid XGBoost model integrated with entropy weight and Bayesian optimization for predicting tunnel squeezing intensity," 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. 119(1), pages 751-771, October.
    10. Helvécio de Oliveira Filho & José Francisco de Oliveira-Júnior & Marcos Vinícius da Silva & Alexandre Maniçoba da Rosa Ferraz Jardim & Munawar Shah & João Paulo Assis Gobo & Claudio José Cavalcante Bl, 2022. "Dynamics of Fire Foci in the Amazon Rainforest and Their Consequences on Environmental Degradation," Sustainability, MDPI, vol. 14(15), pages 1-21, August.
    11. Romulus Costache & Alireza Arabameri & Iulia Costache & Anca Crăciun & Binh Thai Pham, 2022. "New Machine Learning Ensemble for Flood Susceptibility Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4765-4783, September.
    12. Yang, Run & Liu, Xiangui & Yu, Rongze & Hu, Zhiming & Duan, Xianggang, 2022. "Long short-term memory suggests a model for predicting shale gas production," Applied Energy, Elsevier, vol. 322(C).
    13. Tingyu Zhang & Quan Fu & Chao Li & Fangfang Liu & Huanyuan Wang & Ling Han & Renata Pacheco Quevedo & Tianqing Chen & Na Lei, 2022. "Modeling landslide susceptibility using data mining techniques of kernel logistic regression, fuzzy unordered rule induction algorithm, SysFor and random forest," 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. 114(3), pages 3327-3358, December.
    14. Ebrahim Fathi & Danilo Arcentales & Fatemeh Belyadi, 2023. "Impacts of Different Operation Conditions and Geological Formation Characteristics on CO 2 Sequestration in Citronelle Dome, Alabama," Energies, MDPI, vol. 16(7), pages 1-20, April.
    15. Yuto Omae, 2023. "Effects of Exploration Weight and Overtuned Kernel Parameters on Gaussian Process-Based Bayesian Optimization Search Performance," Mathematics, MDPI, vol. 11(14), pages 1-13, July.
    16. Muhammad Bilal & Muhammad Sultan & Faizan Majeed & Muhammad Farooq & Uzair Sajjad & Sobhy M. Ibrahim & Muhammad Usman Khan & Shohreh Azizi & Muhammad Yasar Javaid & Riaz Ahmad, 2022. "Investigating Adsorption-Based Atmospheric Water Harvesting Potential for Pakistan," Sustainability, MDPI, vol. 14(19), pages 1-24, October.
    17. Zefang Zhang & Zhikuan Qian & Yong Wei & Xing Zhu & Linjun Wang, 2022. "Evaluation of Geological Disaster Sensitivity in Shuicheng District Based on the WOE-RF Model," Sustainability, MDPI, vol. 14(23), pages 1-11, December.
    18. Lei, Guoqing & Zeng, Wenzhi & Yu, Jin & Huang, Jiesheng, 2023. "A comparison of physical-based and machine learning modeling for soil salt dynamics in crop fields," Agricultural Water Management, Elsevier, vol. 277(C).
    19. Lei Yang & Mahdi Aghaabbasi & Mujahid Ali & Amin Jan & Belgacem Bouallegue & Muhammad Faisal Javed & Nermin M. Salem, 2022. "Comparative Analysis of the Optimized KNN, SVM, and Ensemble DT Models Using Bayesian Optimization for Predicting Pedestrian Fatalities: An Advance towards Realizing the Sustainable Safety of Pedestri," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    20. Wang, Yanji & Li, Hangyu & Xu, Jianchun & Liu, Shuyang & Tan, Qizhi & Wang, Xiaopu, 2023. "Machine learning assisted two-phase upscaling for large-scale oil-water system," Applied Energy, Elsevier, vol. 337(C).

    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:jsusta:v:14:y:2022:i:22:p:14782-:d:967910. 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.