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• W3189162324 abstract "Uncertainty quantification is an important part of validation, because the pixel scale reference generally suffers from uncertainty caused by different factors, lowering the accuracy of validation results. In order to take a step forward to characterize the uncertainty of validation results, this study proposed a simulated shift-based pixel matching (SSPM) method with the aim of quantifying the uncertainty caused by geometric mismatch in the multiscale validation. Furthermore, its relationships with spatial heterogeneity and subpixel size were also explored. It was found that the uncertainty caused by the geometric mismatch is nonnegligible in multiscale validation, which would obscure the true accuracy of satellite products. Spatial heterogeneity makes a positive contribution to the uncertainty caused by geometric mismatch, but the magnitude depends on subpixel size, being weaker with small subpixel size and stronger with larger subpixel size. Subpixel size is generally positively related to geometric uncertainty. But in the case of very large spatial heterogeneity, their correlation is very weak. This study is an important step toward quantitatively characterizing the uncertainties of pixel scale reference in order to increase the confidence of validation results." @default.
• W3189162324 created "2021-08-16" @default.
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• W3189162324 date "2022-01-01" @default.
• W3189162324 modified "2023-10-12" @default.
• W3189162324 title "Quantification of the Uncertainty Caused by Geometric Registration Errors in Multiscale Validation of Satellite Products" @default.
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• W3189162324 doi "https://doi.org/10.1109/lgrs.2021.3099833" @default.
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