首页> 外文会议>International Geoscience and Remote Sensing Symposium >Improving snow and cloud discrimination in MODIS snow cover products
【24h】

Improving snow and cloud discrimination in MODIS snow cover products

机译:改善MODIS积雪产品中的雪和云歧视

获取原文

摘要

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:中等分辨率成像光谱仪(MODIS)的积雪产品可能会由于云污染,不同的观察几何形状和复杂的表面特性而导致重大错误。为了提高对大传感器视角特别感兴趣的雪和云的辨别力,我们利用重新解释测试来说明时间表面的变化,以丢弃假阳性并恢复假阴性。该方法适用于MODIS分数积雪产品,包括MOD10A1和MODSCAG,然后使用从Landsat-8 Operational Land Imager(OLI)数据生成的参考积雪进行评估。考虑到像素大小的扩展,而不是简单地以标准的500 m空间分辨率实施评估。初步结果表明,该方法显着提高了这两种积雪产品(尤其是MODSCAG)的精度和F评分。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号