Climate Resilience Modeling: Predictive Analytics for Urban Heat Island Mitigation
Main Article Content
Abstract
Urban Heat Island (UHI) intensification has emerged as a critical challenge for climate-resilient urban development, significantly influencing public health, energy consumption, environmental sustainability, and urban livability. The increasing frequency of extreme heat events, coupled with rapid urbanization, necessitates the adoption of advanced predictive frameworks capable of anticipating thermal stress patterns and supporting proactive mitigation strategies. This study proposes a climate resilience modeling framework that integrates predictive analytics, geospatial data, remote sensing observations, machine learning algorithms, and urban environmental indicators to forecast UHI dynamics across heterogeneous urban landscapes. The framework evaluates the relationships among land surface temperature, land-use characteristics, vegetation cover, population density, and built-up infrastructure to identify high-risk thermal hotspots and assess mitigation effectiveness. Predictive models are employed to simulate future heat scenarios and optimize intervention measures such as urban greening, cool roofing systems, reflective pavements, and climate-sensitive urban planning. The proposed approach enhances decision-making by enabling data-driven adaptation strategies that improve urban resilience against escalating climate risks. The study contributes to the growing field of intelligent climate governance by demonstrating how predictive analytics can support sustainable urban heat management, reduce vulnerability, and foster long-term environmental resilience in rapidly expanding cities.
Article Details
Section
How to Cite
References
1. P. Sharma, R. Singh, and N. Yogeswaran, “Global review of urban heat island research across varied climatic regions,” Discover Environment, vol. 4, no. 1, pp. 1–35, 2026.
2. J. Yuan, Y. Zhang, H. Li, and M. Chen, “Urban Heat Island mitigation strategies: A comprehensive review of recent advancements and future directions,” City and Environment Interactions, vol. 30, Art. no. 100258, 2026.
A. N. Ahmed, N. Aldahoul, and N. A. Aziz, “The urban heat island effect: A review on predictive approaches using artificial intelligence models,” City and Environment Interactions, vol. 28, Art. no. 100234, 2025.
A. Q. Syeda, M. Rahman, S. K. Das, and P. Verma, “Sustainable Urban Heat Island mitigation through machine learning-driven climate resilience assessment,” Sustainability, vol. 17, no. 15, Art. no. 7040, 2025.
3. D. Lynda, R. Kouadio, A. Mensah, and J. T. Nguessan, “Hybrid Bayesian deep learning model for predicting urban surface heat island intensity under climate variability,” Scientific Reports, vol. 15, no. 1, pp. 1–18, 2025.
4. Y. Lai, “Urban intelligence for extreme heat mitigation and adaptation,” Tech Monitor, pp. 20–28, 2024.
5. D. Jato-Espino, C. Manchado, A. Roldán Valcarce, and V. Moscardó, “ArcUHI: A GIS add-in for automated modelling of the Urban Heat Island effect through machine learning,” Sustainable Cities and Society, vol. 83, Art. no. 103950, 2022.
6. Y. Yao, C. Chang, F. Ndayisaba, and S. Wang, “A new approach for surface urban heat island monitoring based on machine learning algorithm and spatiotemporal fusion model,” IEEE Access, vol. 8, pp. 164268–164281, 2020.
7. J. Voelkel and V. Shandas, “Towards systematic prediction of urban heat islands: Grounding measurements, assessing modeling techniques,” Climate, vol. 5, no. 2, Art. no. 41, 2017.
8. Q. Weng, D. Lu, and J. Schubring, “Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies,” Remote Sensing of Environment, vol. 89, no. 4, pp. 467–483, 2004.
A. Shrivastava, S. Bhadula, R. Kumar, G. Kaliyaperumal, B. D. Rao and A. Jain, "AI in Medical Imaging: Enhancing Diagnostic Accuracy with Deep Convolutional Networks," 2025 International Conference on Computational, Communication and Information Technology (ICCCIT), Indore, India, 2025, pp. 542-547, doi: 10.1109/ICCCIT62592.2025.10927771.
9. S. Hundekari, A. Shrivastava, R. Praveen, R. H. C. Alfilh, A. Badhoutiya and N. Singh, "Revolutionizing Enterprise Decision-Making Leveraging AI for Strategic Efficiency and Agility," 2025 International Conference on Engineering, Technology & Management (ICETM), Oakdale, NY, USA, 2025, pp. 1-6, doi: 10.1109/ICETM63734.2025.11051858.
A. Shrivastava, R. Praveen, R. Aida, K. Vemuri, S. S. Vemuri and S. O. Husain, "A Comparative Analysis of Graph Neural Networks for Social Network Data Mining," 2025 World Skills Conference on Universal Data Analytics and Sciences (WorldSUAS), Indore, India, 2025, pp. 1-6, doi: 10.1109/WorldSUAS66815.2025.11199244.
A. Shrivastava, R. Praveen, R. R. Al-Fatlawy, S. Bansal, S. Lakhanpal and J. K. K. Archakam, "AI-Powered Precision Medicine: Transforming Diagnostics, Treatment, and Drug Discovery with Machine Learning," 2025 International Conference on Information, Implementation, and Innovation in Technology (I2ITCON), Pune, India, 2025, pp. 1-6, doi: 10.1109/I2ITCON65200.2025.11210611.
10. V. Nutalapati, R. Aida, S. S. Vemuri, N. Al Said, A. M. Shakir and A. Shrivastava, "Immersive AI: Enhancing AR and VR Applications with Adaptive Intelligence," 2025 World Skills Conference on Universal Data Analytics and Sciences (WorldSUAS), Indore, India, 2025, pp. 1-6, doi: 10.1109/WorldSUAS66815.2025.11199210.
11. L. Chawla, A. Shrivastava, M. I. Habelalmateen, H. Shekhar, P. Mittal and S. Sharma, "Federated Foundation Models for Healthcare Diagnostics," 2025 2nd International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), Raipur, India, 2025, pp. 1-6, doi: 10.1109/ICAIIHI67124.2025.11403022.
12. V. Nimbalkar, L. Chawla, M. M. Adnan, A. Bhansali, M. Gupta and R. Kalra, "A Human-Centered Approach to Interpretable Machine Learning in Clinical Decision Support Systems," 2025 2nd International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), Raipur, India, 2025, pp. 1-5, doi: 10.1109/ICAIIHI67124.2025.11403473.
13. D. Chawla, D. Chawla, A. Shrivastava, M. I. Habelalmateen, M. Dixit and S. P. Dwivedi, "Explainable AI for Mental Health Diagnosis: Enhancing Transparency, Trust, and Clinical Decision-Making," 2025 2nd International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI), Raipur, India, 2025, pp. 1-6, doi: 10.1109/ICAIIHI67124.2025.11403514
14. D. Chawla, D. Chawla, A. Shrivastava, M. M. Adnan, B. Sireesha and I. Khan, "Blockchain and Federated Learning Integration for Secure IoT and Cyber-Physical Systems," 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG), Indore, Madhya Pradesh, India, India, 2025, pp. 1-7, doi: 10.1109/ICTBIG68706.2025.11323990.
15. Chawla, D. Chawla, A. Shrivastava, M. M. Adnan, B. Sireesha and I. Khan, "AI-Driven Predictive Infrastructure for Smart and Sustainable Cities," 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG), Indore, Madhya Pradesh, India, India, 2025, pp. 1-7, doi: 10.1109/ICTBIG68706.2025.11324009.
16. Saxena, P., and Saxena, V. (2022). “Comparative Study of White Gaussian Noise Reduction for Different Signals Using Wavelet”. International Journal of Research -GRANTHAALAYAH, 10(7), 112–123. https://doi.org/10.29121/granthaalayah.v10.i7.2022.4711
17. Saxena Parul, Umang Saini, and Vinay Saxena. "Design and implementation of sound signal reconstruction algorithm for blue hearing system using wavelet." Automation and Computation. CRC Press, 2023. 405-411.
18. K. Himabindu, V. Saxena, S. P, K. K, E. Sathish and D. Suganthi, "IoT–Fuzzy Logic Hybrid Framework for Crop Monitoring and Yield Prediction in Smart Agriculture," 2025 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS), Hassan, India, 2025, pp. 1-6, doi: 10.1109/IACIS65746.2025.11211067.
19. Saxena Vinay. (2012) “Fourier Descriptors under Rotation, Scaling, Translation and Various Distortion for Hand Drawn Planar Curves”. Journal of Experimental Sciences, vol. 3, no. 1, 05-07. https://updatepublishing.com/journal/index.php/jes/article/view/1905.
20. Saxena Vinay, and Kapoor V.V., (2011), “Behavior of Normalized Moments under Distortion and Optimization, Recent Research in Science and Technology”, 3(7),73-76. https://updatepublishing.com/journal/index.php/rrst/article/view/743
21. Vinay Saxena, (2014), “International Journal of Emerging Technologies in Computational and Applied Sciences”, 9(2), 170-175. https://iasir.net/files/ijetcaspapers/ijetcas14-567.pdf
22. Saxena, P., Saxena, V., Basvant, M. S. Lohumi, Y.Saraswat, M. Sankhyan, A. Deepak, A. and Shrivastava, A.. (2024) “Fuzzy-Based Medical Image Processing and Analysis”, International Journal of Intelligent Systems and Applications in Engineering, 12(16s), pp. 320–327.
23. Saxena, V.,Singh, M., Saxena, P., Singh, M., Srivastava, A. P., Kumar, N., Deepak, A.& Shrivastava, A.. (2024). “Utilizing Support Vector Machines for Early Detection of Crop Diseases in Precision Agriculture a Data Mining Perspective”. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 281–288.
24. P. Bagane, S. G. Joseph, A. Singh, A. Shrivastava, B. Prabha and A. Shrivastava, "Classification of Malware using Deep Learning Techniques," 2021 9th International Conference on Cyber and IT Service Management (CITSM), Bengkulu, Indonesia, 2021, pp. 1-7, doi: 10.1109/CITSM52892.2021.9588795.
25. Attar T. V., & Momin S. (2025). Nanotechnology in drug delivery: Challenges and future prospects. Advances in Bioresearch, 16(2), 63–69.
26. Das B., Attar T. V., Sharma N., Sharma R., Anandhan A., & Acharya S. (2025). Biochemistry to solve environmental degradation and sustainable future. International Journal of Environmental Sciences, 11(20s), 2527–2545. https://doi.org/10.64252/bz71eq58 80. Dhanke J., Attar T. V. & Zode, P. (2025). Optimal transport theory in machine learning: Applications to generative modelling and domain adaptation. International Journal of Environmental Sciences, 11(21s), 2613–2630.
27. Divate S., Attar T. V., Patil M. A., Yadav T. P., & Wagh G. D. (2025). Synthesis and characterization applications of nanoparticles for photocatalytic degradation of organic dyes. International Journal of Environmental Sciences, 11(23s), 695–712. https://doi.org/10.64252/n0shfg48
28. Attar T. V. (2022). Investigations on enhanced DC conductivity and dielectric properties by rare earth doping of lanthanum fluoride. Shodhasamhita, 9(2), 180–184.
29. Attar T. V. (2022). Studies on cytotoxicity of LaF3: Pr, Ho nanoparticles for possible biomedical applications. Shodhasamhita, 9(2/1), 254–257.
30. Dr. Mohd. Talib Ather Ansari, (2025). “One Nation One Subscription' Digital Library Resources to Enrich Teacher Educators for Practical knowledge and Foster an Engaging Teaching-Learning Ecosystem” South eastern European Journal of Public Health, ISSN: 2197-5248, Volume XXVI, S1, 2025, P. 7166-7181, Published by- Uphill’s Publishers LLC, Sheridan, Wyoming, United States. DOI: https://doi.org/10.5281/zenodo.16325646 Available at https://seejph.com/index.php/seejph/article/view/6671/4424
31. Dr. Hina Hasan, & Dr. Mohd. Talib Ather Ansari, (2025). “Techno-Pedagogical Practices in Inclusive Education: Comparing Approaches for Slow Learners across Teacher Education Programme” TPM - Testing, Psychometrics, Methodology in Applied Psychology, (Scopus Q3 journal), ISSN- 1972-6325, Impact Factor- 0.505, Vol-32, Page from 222-235-2025, Published by Cises DOI: https://doi.org/10.5281/zenodo.17746118 Available at https://tpmap.org/submission/index.php/tpm/article/view/3162/2364
32. Dr. Mohd. Talib Ather Ansari, & Dr. Hina Hasan. (2024). “Need And Importance of Translation of Indian Languages Vice Versa to Promote Indian Educational Scenario”. Educational Administration: Theory and Practice, 30(1), ISSN:1300-4832E-
33. S. N. Siri, H. B. Divyashree, and S. P. Mala, "The Memorable Assistant: An IoT-Based Smart Wearable Alzheimer's Assisting Device," in Proc. 5th Int. Conf. Comput. Syst. Inf. Technol. Sustain. Solut. (CSITSS), 2021. DOI: 10.1109/CSITSS54238.2021.9682788
34. D. H. Balachandra, P. C. Gowda, and N. P. K. Shivaprasad, "Secure Cluster-Based Routing Using Multi Objective-Trust Centric Artificial Algae Algorithm for Wireless Sensor Network," Int. J. Electr. Comput. Eng., vol. 13, no. 2, pp. 1618–1628, 2023, DOI: https://doi.org/10.11591/ijece.v13i2.pp1618-1628
35. H. B. Divyashree, C. Puttamadappa, and K. S. Nandini Prasad, "Performance Analysis and Enhancement of QoS Parameters for Real-Time Applications in MANETs-Comparative Study," in Proc. 5th IEEE Int. Conf. Recent Trends Electron. Inf. Commun. Technol. (RTEICT), 2020, pp. 256–260, DOI: 10.1109/RTEICT49044.2020.9315547
36. V. H. Patil, A. Shrivastava, D. Verma, A. L. N. Rao, P. Chaturvedi and S. V. Akram, "Smart Agricultural System Based on Machine Learning and IoT Algorithm," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), Tashkent, Uzbekistan, 2022, pp. 740-746, doi: 10.1109/ICTACS56270.2022.9988530.
37. S. Chakaborty, Y. D. Borole, A. S. Nanoty, A. Shrivastava, S. K. Jain and M. L. Rinawa, "Smart Remote Solar Panel Cleaning Robot with Wireless Communication," 2021 9th International Conference on Cyber and IT Service Management (CITSM), Bengkulu, Indonesia, 2021, pp. 1-5, doi: 10.1109/CITSM52892.2021.9588917.
A. Rana, V. Khurana, A. Shrivastava, D. Gangodkar, D. Arora and A. Kumar Dixit, "A ZEBRA Optimization Algorithm Search for Improving Localization in Wireless Sensor Network," 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), Tashkent, Uzbekistan, 2022, pp. 817-824, doi: 10.1109/ICTACS56270.2022.9988278.
38. S. Hundekari, R. Praveen, A. Shrivastava, R. R. Hwsein, S. Bansal and L. Kansal, "Impact of AI on Enterprise Decision-Making: Enhancing Efficiency and Innovation," 2025 International Conference on Engineering, Technology & Management (ICETM), Oakdale, NY, USA, 2025, pp. 1-5, doi: 10.1109/ICETM63734.2025.11051526
39. R. Praveen, A. Shrivastava, G. Sharma, A. M. Shakir, M. Gupta and S. S. S. R. G. Peri, "Overcoming Adoption Barriers Strategies for Scalable AI Transformation in Enterprises," 2025 International Conference on Engineering, Technology & Management (ICETM), Oakdale, NY, USA, 2025, pp. 1-6, doi: 10.1109/ICETM63734.2025.11051446.