Abstract
Snow cover has a significant impact on numerous ecological, climatic, and hydrological processes, particularly in high-latitude areas. Remote sensing data estimates of snow cover ranges than traditional surveying methods. Thus, the present study used Sentinel-2B satellite images to compare the performance of support vector machine (SVM) kernel functions and object-oriented fuzzy operators to estimate the snow cover area (SCA) on Alvand Mountain. The research data included four Sentinel-2B 10 m spatial resolution bands (B2, B3, B4, and B8) that were launched on March 6, 2020. In this study, linear, polynomial, radial, and sigmoid SVM kernel functions, as well as the object-oriented fuzzy operators (AND, OR, MGE, MAR, MGWE, and ALP), were used. The results indicated that AND algorithm, which represents a logical commonality, had the lowest return fuzzy value of 98% compared to other algorithms, thus, providing the overall highest accuracy. Based on these findings, the object-oriented processing method in digital image classification could provide the highest accuracy compared to the SVM kernel functions; that is because a wide range of information, such as texture, shape, position, content, and bandwidth, is associated with the objects in this classification method. Finally, the SCA in Alvand Mountain was estimated to be 604 km2 based on the object-based AND fuzzy operator.
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Abbreviations
- OBIA:
-
Object-based image analysis
- RS:
-
Remote sensing
- SCA:
-
Snow cover area
- SLT:
-
Statistical learning theory
- SVM:
-
Support vector machine
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MK and AHalabian designed the project. All authors analyzed the data and wrote the manuscript. All authors approved the final version of the manuscript.
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Karampour, M., Halabian, A., Hosseini, A. et al. Comparing the performance of fuzzy operators in the object-based image analysis and support vector machine kernel functions for the snow cover estimation in Alvand Mountain. Theor Appl Climatol 155, 1729–1737 (2024). https://doi.org/10.1007/s00704-023-04724-6
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DOI: https://doi.org/10.1007/s00704-023-04724-6