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Improving snow and cloud discrimination in MODIS snow cover products

机译:改善MODIS雪盖产品中的雪和云歧视

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The Moderate Resolution Imaging Spectroradiometer (MODIS) fractional snow cover products may have significant errors due to cloud contamination, varying viewing geometry and complex surface properties. To improve snow and cloud discrimination with a particular interest in large sensor viewing angles, we utilize a reinterpretation test accounting for temporal surface variability to discard false positives and recover false negatives. This method is applied to MODIS fractional snow cover products including MOD10A1 and MODSCAG, then evaluated with reference snow cover generated from Landsat-8 Operational Land Imager (OLI) data. Rather than simply implementing evaluation at the normative 500 m spatial resolution, the expansion of pixel size is considered. Preliminary results indicate that this method significantly improves the precision and F-score of these two snow cover products, especially MODSCAG.
机译:由于云污染,不同观察几何形状和复杂的表面性质,适度分辨率成像分光镜(MODIS)分数雪覆盖产品可能具有显着的误差。为了改善对大型传感器观察角度的特殊兴趣的雪和云歧视,我们利用重新解释试验算法进行时间表面可变性,以丢弃误报并恢复错误的否定。该方法适用于Modis分数雪覆盖产品,包括MOD10A1和MODSCAG,然后用来自Landsat-8运行陆地成像器(OLI)数据产生的参考雪盖评估。考虑不考虑以像素大小的扩展以规范500μm空间分辨率来实现评估。初步结果表明,该方法显着提高了这两个雪覆盖产品,尤其是ModScag的精度和F分。

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