Abstract
In this paper, a new decision-making model is suggested to be applied when choosing satellite imagery analysis tools in climatic monitoring uses. The method combines the Weighted Aggregated Sum Product Assessment (WASPAS) model with Dombi aggregation operators in the context of the spherical fuzzy set that is successfully used to address the uncertainty, hesitation and imprecision common in expert ratings. The criteria used to select the key decisions are the accuracy of the resolution, efficiency in time, the ability to integrate data, and the applicability in climate analysis. Spherical fuzzy sets improve the ability of the model to deal with vague information and the use of Dombi operators enables the aggregation behavior to be adjusted. The effectiveness and strength of the proposed method is confirmed and proven in a case study and comparative analysis. The findings point to its applicability as a valid and total strategy of technology choice in environmental as well as remote sensing arenas.
Similar content being viewed by others
Data availability
The datasets generated and analysed during the current study are included in this article and its supplementary information files. All data used to support the findings of this study are provided within the manuscript.
References
Laha, B., Pal, S. & Das, S. Land cover classification using fuzzy rules and contextual aggregation. Int. J. Remote Sens. 30(18), 4567–4584 (2009).
Rahman, S. & Ahmed, M. Comparative study of spherical fuzzy MCDM methods in water resource management. J. Environ. Inf. 27 (1), 45–58 (2021).
Chen, L. & Fan, Y. Spherical fuzzy Yager aggregation in renewable energy selection. Energy and AI 3, 100023 (2020).
Liu, Q., Chen, S. & Wang, X. Adaptive evaluation of edge-detection algorithms via neutrosophic WASPAS. MDPI Remote Sensing 12(7), 1123 (2020).
Belton, V. & Stewart, T. J. Multiple criteria decision analysis: An integrated approach (Kluwer Academic, 2002).
Hwang, C. L. & Yoon, K. Multiple attribute decision making: Methods and applications (Springer-, 1981).
Triantaphyllou, E. Multi-criteria decision making: A comparative study 2nd edn (Springer, 2000).
Zadeh, L. A. Fuzzy sets. Inf. Control 8(3), 338–353 (1965).
Zavadskas, E. K. & Mardani, A. Development of TOPSIS-based methods in multi-criteria decision making: An overview. Int. J. Inf. Technol. Decis. Mak. 15(5), 827–852 (2016).
Zhong, Y., Gao, H. & Guo, X. Dombi power aggregation operators for q-rung orthopair fuzzy numbers. Int. J. Fuzzy Syst. 21 (4), 1091–1103 (2019).
Ashraf, S., Abdullah, S. & Mahmood, T. Spherical fuzzy Dombi aggregation operators and their application in group decision making problems. J. Decis. Syst. 28(3), 150–167 (2019).
Karaaslan, F. & Dawood, M. A. D. Complex T-spherical fuzzy Dombi aggregation operators and their applications to multi-attribute decision making. J. Intell. Fuzzy Syst. 40 (2), 2153–2164 (2021).
Shaban, A., Liu, H. & Muhammad, K. New aggregation functions for spherical fuzzy sets and their application to MULTIMOORA. Journal of Multi-Criteria Decision Analysis 29(2), 120–134 (2022).
Ullah, K., Mahmood, T. & Garg, H. Correlation coefficients for T-spherical fuzzy sets: Applications in multi-attribute decision making. Soft. Comput. 24 (14), 10417–10428 (2020).
Wang, X., Li, G. & Mahmood, T. A novel study of spherical fuzzy soft Dombi aggregation operators and their applications to multicriteria decision making. Appl. Soft Comput. 125, 109300 (2023).
Diwan, M. & Singh, A. Advanced linguistic complex T-spherical fuzzy WASPAS with Dombi weighting. J. Comput. Intell. 38 (8), 1452–1465 (2021).
Senapati, T. & Chen, G. Picture fuzzy WASPAS technique and its application in supplier evaluation. IEEE Trans. Fuzzy Syst. 30 (5), 910–922 (2022).
Singh, R., Kumar, S. & Gupta, P. Solar panel selection via CASPAS: Choquet and WASPAS under disc intuitionistic fuzzy sets. Sustainable Energy Reviews 45(6), 156–168 (2021).
Mwangi, E. & Owino, T. Qualitative rating of lossy compression for aerial imagery based on neutrosophic MCDM. MDPI Sensors 16(4), 2345 (2022).
Oliveira, P., Souza, J. & da Silva, R. Neutrosophic WASPAS for satellite image edge detection tool selection. Journal of Computational Vision 9(1), 45–60 (2021).
Solgi, E., Gitinavard, H. & Tavakkoli-Moghaddam, R. Sustainable high-tech brick production with energy-oriented consumption: An integrated possibilistic approach based on criteria interdependencies. Sustainability 14 (1), 202 (2021).
Ghaderi, H., Gitinavard, H. & Mehralizadeh, M. An intuitionistic fuzzy DEA cross-efficiency methodology with an application to production group decision-making problems. J. Qual. Eng. Prod. Optim. 5 (2), 69–86 (2020).
Gitinavard, H., Moosavi, S. M., Vahdani, B. & Ghaderi, H. A new decision making method based on hesitant fuzzy preference selection index for contractor selection in construction industry. (2017).
Behzadipour, A., Gitinavard, H. & Akbarpour Shirazi, M. A novel hierarchical dynamic group decision-based fuzzy ranking approach to evaluate the green road construction suppliers. Sci. Iran. https://doi.org/10.24200/sci.2022.58112.5571 (2022).
Nezami, M., Gitinavard, H. & Zade, A. E. Soft computing-based new dynamic intuitionistic fuzzy group decision analysis for risk evaluation in BOT highway construction projects. Operational Research 25(2), 56 (2025).
Dhumras, H. & Bajaj, R. K. On potential strategic framework for green supply chain management in the energy sector using q-rung picture fuzzy AHP & WASPAS decision-making model. Expert Syst. Appl. 237, 121550 (2024).
Pal, M., Dhumras, H., Garg, G. & Shukla, V. On renewable energy source selection problem using T-spherical fuzzy soft Dombi aggregation operators. Sustainable Mobility: Policies Challenges Advancements, 237–253. (2024).
Dhumras, H., Kumar, M. & Bajaj, R. K. Effectiveness of debris flow mitigation measures through T-spherical fuzzy soft dombi aggregation operators with EDAS-based multi-criteria decision making in mountainous regions. J. Ind. Inf. Integr. https://doi.org/10.1016/j.jii.2025.100968 (2025).
Dhumras, H. & Bajaj, R. K. Modified EDAS method for MCDM in robotic agrifarming with picture fuzzy soft Dombi aggregation operators. Soft Comput 27(8), 5077–5098 (2023).
Dhumras, H. & Bajaj, R. K. On prioritization of hydrogen fuel cell technology utilizing bi-parametric picture fuzzy information measures in VIKOR & TOPSIS decision-making approaches. Int. J. Hydrogen Energy 48(96), 37981–37998 (2023).
Nasir, M., Mahmood, T. & Khan, A. Spherical fuzzy credibility Dombi aggregation operators: Theory and applications in decision making. Inf. Sci. 588, 110–127 (2022).
Zhou, X., Wang, Z. & Chen, Y. Disc spherical fuzzy WASPAS approach with Dombi operators. Proceedings of the International Conference on Fuzzy Systems, 112–119. (2025), April.
Abbas Mardani, A. et al. Fuzzy multiple criteria decision-making techniques in logistics and supply chain management: A review of applications. Int. J. Adv. Manuf. Technol. 78(1–4), 561–578 (2015).
Ali, S. & Khan, D. T-spherical fuzzy information aggregation in group decision making. J. Decis. Anal. 6(2), 89–102 (2023).
Ching–Lai Hwang, Y. J., Lai & Liu, T. Y. An approach to multi-objective decision making using fuzzy measures and fuzzy integrals. Comput. Oper. Res. 20 (6), 563–573 (1993).
Lopez, J. & Martinez, F. Consensus-based intuitionistic fuzzy WASPAS (c-WASPAS) for supplier evaluation. Decis. Support Syst. 131, 113–124 (2020).
Kapoor, R. & Sharma, V. AHP-WASPAS under spherical fuzzy sets for hospital selection. Int. J. Med. Inform. 152, 104–114 (2022).
Schmidt, L. & Springer, B. Decision support based on spherical fuzzy Yager aggregation for wind power project selection. J. Renew. Energy. 50 (3), 255–268 (2020).
Tang, L., Xu, H. & Ma, B. Picture fuzzy WASPAS application in smart manufacturing. IEEE Trans. Ind. Inf. 18(9), 5895–5905 (2022).
Ullah, K., Mahmood, T., Ahmad, J. & Ali, A. T-spherical fuzzy Hamacher aggregation operators for search and rescue robots. IEEE Access 8, 134569–134580 (2020).
Author information
Authors and Affiliations
Contributions
R. Vinod Kumar conceptualized the study, developed the spherical fuzzy WASPAS–Dombi methodology, carried out the theoretical analysis, and drafted the original manuscript.P. Hemavathi contributed to the mathematical formulation, validation of the proposed operators and assisted in manuscript revision.P. Muralikrishna performed the numerical analysis, comparative study with existing MCDM methods, and interpretation of results.Hasan Dincer contributed to the decision-making framework design, application perspective, and critical review of the methodology.Serhat Yuksel assisted with the case study design, data analysis, visualization of results, and manuscript editing.All authors reviewed the manuscript, discussed the results, and approved the final version.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Vinod Kumar, R., Hemavathi, P., Muralikrishna, P. et al. A spherical fuzzy WASPAS approach with Dombi aggregation for satellite imagery tool selection in climate monitoring applications. Sci Rep (2026). https://doi.org/10.1038/s41598-026-48877-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-48877-6
