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- W2916925535 abstract "Separation of clouds from snow and ice is fundamentally very challenging because these features display very similar spectral characteristics. To investigate how to improve the separation of these features using the fractal summation method and spatial point-pattern analysis, Landsat 8 Operational Land Imager (OLI) images containing both cloud and snow/ice were used as a data source. Selective principal component analysis (SPCA) was applied to those bands sensitive to information regarding cloud and snow, and the fractal summation method and spatial point-pattern analysis were then applied. This innovative cloud detection method was found to be an effective tool for reducing non-cloud false anomalies in images where snow and ice share similar spectra with clouds." @default.
- W2916925535 created "2019-03-02" @default.
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- W2916925535 date "2019-01-01" @default.
- W2916925535 modified "2023-10-16" @default.
- W2916925535 title "Cloud Detection in Landsat Imagery Using the Fractal Summation Method and Spatial Point-Pattern Analysis" @default.
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- W2916925535 doi "https://doi.org/10.1007/978-981-13-7025-0_21" @default.
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