Satellite Sensing for Sea Level Monitoring: A Transformative Approach to Understanding Climate Change

Year : 2025 | Volume : 12 | Issue : 01 | Page : 29 37
    By

    Dr Kazi Kutubuddin S. L.,

  • Dr. G M Kosgiker,

  1. Professor, Department of Electronics and Telecommunication Engineering, Brahmadanda Mane Institute of Technology, Solapur, Maharashtra, India
  2. Professor, Department of Electronics and Telecommunication Engineering, Brahmadanda Mane Institute of Technology, Solapur, Maharashtra, India

Abstract

Satellite sensing becomes an essential tool for risk assessment and management as coastal communities continue to struggle with the numerous threats posed by climate change. By using this technology, environmental scientists, legislators, and urban planners may make better judgements that will result in coastal towns that are safer and more resilient. A major advancement in reducing the effects of extreme weather, environmental degradation, and rising sea levels has been made with the incorporation of satellite data into urban planning and disaster preparedness initiatives. Resilience and adaptation are not just choices; they are essentials, and satellite sensing offers the means to successfully achieve them. Sea level monitoring has been revolutionized by satellite sensing, which provides vital information that helps us comprehend how climate change affects sea levels worldwide. Satellite observations will become ever more important as technology develops to support climate resilience plans and assist vulnerable people worldwide. A new era in environmental monitoring is being fostered by the combination of cutting-edge sensing techniques, teamwork, and improved data accessibility, all of which are crucial for preserving the future of our planet.

Keywords: Satellite Sensing, Sea level, Climate change, coastal areas, environmental study.

[This article belongs to Journal of Microwave Engineering and Technologies ]

How to cite this article:
Dr Kazi Kutubuddin S. L., Dr. G M Kosgiker. Satellite Sensing for Sea Level Monitoring: A Transformative Approach to Understanding Climate Change. Journal of Microwave Engineering and Technologies. 2025; 12(01):29-37.
How to cite this URL:
Dr Kazi Kutubuddin S. L., Dr. G M Kosgiker. Satellite Sensing for Sea Level Monitoring: A Transformative Approach to Understanding Climate Change. Journal of Microwave Engineering and Technologies. 2025; 12(01):29-37. Available from: https://journals.stmjournals.com/jomet/article=2025/view=193380


References

1. Mahmoudi C, Flah A, Sbita L. Prototype design of a compact plug-in solar electric vehicle application for smart power management architecture. 2017 International Conference on GreenEnergyConversionSystems(GECS),Hammamet, Tunisia. 2017; 1–4. doi:10.1109/GECS.2017.8066162.
2. Khandelwal A, Kumar J. Applications of AI for Power Electronics and Drives Systems: A Review.2019 Innovations in Power and Advanced Computing Technologies (i-PACT), Vellore, India. 2019; 1–6. doi: 10.1109/i-PACT44901.2019.8960123.
3. Khadake Suhas B. Detecting Salient Objects of Natural Scene in a Video’s Using Spatio-Temporal Saliency & Colour Map. Journalnx – A Multidisciplinary Peer Reviewed Journal. 2021; 2(08): 3035. Retrieved From Https://Repo.Journalnx.Com/Index.Php/Nx/Article/View/1070
4. Mallad HM, et al. A Comprehensive Analysis Of Artificial Intelligence Integration In Electrical Engineering. 2024 5th International Conference On Mobile Computing And Sustainable Informatics (Icmcsi), Lalitpur, Nepal. 2024; 484–491. Doi: 10.1109/Icmcsi61536.2024.00076.
5. Kawade S, Moholkar S, Pawar M. A Review of 6g Technologies and Its Advantages Over 5g Technology. In: Pawar PM, et al. Techno-Societal 2022. Icatsa 2022. Cham: Springer; 2024. Https://Doi.Org/10.1007/978-3-031-34644-6_107
6. Balkrishna Dudgikar A, Ahmad Akbar Ingalgi A, Gensidha Jamadar A, et al. Intelligent Battery Swapping System For Electric Vehicles With Charging Stations Locator On Iot And Cloud Platform. Int J Adv Res Sci Commun Technol. 2023 Jan; 3(1): 204–208. Doi: 10.48175/Ijarsct7867. Available At: Https://Ijarsct.Co.In/Paper7867.Pdf Map.
7. Khadake Suhas B. Detecting Salient Objects in a Video’s By Using Spatio-Temporal Saliency & ColourInt J Innov EnRes
Technol. 2021;3(8):1–9.Https://Repo.Ijiert.Org/Index.Php/Ijiert/Article/View/910.
8. Kashid Pranita J, Kawade Asmita M, Khedekar Santoshi V, Mallad HM. Electric Vehicle Technology Battery Management – Review. Int J Adv Res Sci Commun Technol. 2023 Sep; 3(2): 319–325. Https://Doi.Org/10.48175/Ijarsct-13048.
9. Karale Nikita, Jadhav Supriya, et al. Design of Vehicle system using CAN Protocol. Int J Res Appl Sci Eng Technol. 2020; 8(V): 1978–1983. http://doi.org/10.22214/ijraset.2020.5321.

10. Kazi Sultanabanu Sayyad Liyakat. Accepting Internet of Nano-Things: Synopsis, Developments,and Challenges. Journal of Nanoscience, Nanoengineering & Applications (JoNSNEA). 2023;13(2): 17–26. DOI:https://doi.org/10.37591/jonsnea.v13i2.1464.Tools
11. Kazi Kutubuddin Sayyad Liyakat. Home Automation System Based on GSM. Journal of VLSI
Design&Technology(JoVDTT).2023k;13(3):7–12.https://doi.org/10.37591/jovdtt.v13i3.7877.
12. Liyakat KKS. Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Udgata SK, Sethi S, Gao XZ, editors. Intelligent Systems. ICMIB 2023.Lecture Notes in Networks and Systems. Vol. 728. Singapore: Springer; 2024.https://doi.org/10.1007/978-981-99-3932-9_12availableat:https://link.springer.com/chapter/10.1007/978-981-99-3932-9_12
13. Liyakat KKS. Detecting Malicious Nodes in IoT Networks Using Machine Learning and Artificial Neural Networks. 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India. 2023; 1–5. doi: 10.1109/ESCI56872.2023.10099544.
14. Kasat K, Shaikh N, Rayabharapu VK, Nayak M. Implementation and Recognition of Waste Management System with Mobility Solution in Smart Cities using Internet of Things. 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India. 2023; 1661–1665. doi: 10.1109/ICAISS58487.2023.10250690
15. Liyakat KKS. Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Shukla PK, Mittal H, Engelbrecht A, editors. Computer Vision and Robotics. CVR 2023. Algorithms for Intelligent Systems. Singapore: Springer; 2023. https://doi.org/10.1007/978-981-99-4577-1_3
16. Kazi K. AI-driven IoT (AIIoT) in healthcare monitoring. In: Nguyen T, Vo N, editors. Using Traditional Design Methods to Enhance AI-Driven Decision Making. Pennsylvania (PA): IGI Global; 2024. p. 77–101. DOI: 10.4018/979-8-3693-0639-0.ch003.
17. Kazi K. Modelling and simulation of electric vehicle for performance analysis: BEV and HEV electricalvehicle implementation using Simulink for e-mobility ecosystems. In: LD, Nagpal N, Kassarwani N,Varthanan GV, Siano P, editors. E-mobility in Electrical Energy Systems for Sustainability.Pennsylvania (PA): IGI Global; 2024. p. 295–320. DOI: 10.4018/979-8-3693-2611-4.ch014.
18. Magadum Prashant K. Machine Learning for Predicting Wind Turbine Output Power in WindEnergy Conversion Systems. Grenze International Journal of Engineering and Technology(GIJET). 2024 Jan; 10(1): 2074–2080. Grenze ID: 01.GIJET.10.1.4_1 Available at:https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8
19. Neeraja P, Kumar RG, Kumar MS, Liyakat KKS, Vani MS. DL-Based Somnolence Detection forImproved Driver Safety and Alertness Monitoring. 2024 IEEE International Conference onComputing, Power and Communication Technologies (IC2PCT), Greater Noida, India. 2024; 589594. doi: 10.1109/IC2PCT60090.2024.10486714. Available at:https://ieeexplore.ieee.org/document/10486714
20. Saraswat D, Bhattacharya P, Verma A, Prasad VK, Tanwar S, Sharma G, Bokoro PN, Sharma R.Explainable AI for healthcare 5.0: opportunities and challenges. IEEE Access. 2022 Aug 8; 10:84486–517.
21. Veena C, Sridevi M, Saha B, Reddy SR, Shirisha N. HEECCNB: An Efficient IoT-Cloud Architecture for Secure Patient Data Transmission and Accurate Disease Prediction in HealthcareSystems. 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan,
India.2023;407–410.doi:10.1109/ICIIP61524.2023.10537627.Availableat:https://ieeexplore.ieee.org/document/10537627
22. Rajendra Prasad K, Santoshachandra Rao Karanam. AI in public-private partnership for IT infrastructure development. J High Technol Manag Res. 2024 May; 35(1): 100496. https://doi.org/10.1016/j.hitech.2024.100496
23. Megha Nagrale, Pol Rahul S, Birajadar Ganesh B, Mulani Altaf O. Internet of Robotic Things in Cardiac Surgery: An Innovative Approach. Afr J Biol Sci. 2024; 6(6): 709–725. doi: 10.33472/AFJBS.6.6.2024.709-725

Regular Issue Subscription Review Article
Volume 12
Issue 01
Received 13/12/2024
Accepted 18/12/2024
Published 10/01/2025
Publication Time 28 Days
255

Login


My IP

PlumX Metrics