Cloud and Snow Detecting and Removing in SPOT VEGETATION Images

LIU Yong-mei; WANG Chao; YU Dong

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Cloud and Snow Detecting and Removing in SPOT VEGETATION Images

- Cloud and Snow Detecting and Removing in SPOT VEGETATION Images
- Bulletin of Soiland Water Conservation Vol. 29, Issue 2, Pages: 236-238(2010)
- 作者机构：
  
  西北大学城市与环境学院,陕西,西安,710127
- 作者简介：
- 基金信息：
- DOI：
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- Published：2010
- 稿件说明：
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LIU Yong-mei, WANG Chao, YU Dong. Cloud and Snow Detecting and Removing in SPOT VEGETATION Images[J]. Bulletin of Soiland Water Conservation, 2010, 29(2): 236-238.
DOI：

LIU Yong-mei, WANG Chao, YU Dong. Cloud and Snow Detecting and Removing in SPOT VEGETATION Images[J]. Bulletin of Soiland Water Conservation, 2010, 29(2): 236-238. DOI：

摘要

以整个中国区域为例，采用3种检测方法对Spot vegetation S10影像上存在的云和雪盖的检测结果进行了对比分析。结果表明，BISE检测器得到的云层和实际最为接近，用Spot vegetation状态地图得到的云层过少，而用Spot vegetation检测器V2.0得到的云和雪盖像素有部分重叠。最后利用云、雪盖像素在时间序列上的相邻像素进行平滑处理方法达到去云和雪盖的目的，研究结果对于Spot vegetation S10影像的噪音消除和应用精度的提高具有借鉴意义。

Abstract

Taking China as the test area

the three kinds of methods for detecting the cloud and snow on Spot Vegetation S10 images are compared. According to the comparison

BISE is the best for detecting cloud among the three; the cloud extracted by the status map (SM) is too little; cloud and the ice and snow extracted by the detector V2.0 overlap each other. The averaging of timely neighboring (before and after the cloud pixels) cloudy (or ice and snow)-free pixels is adopted to remove cloud

ice

and snow. The result is valuable for noise reduction and application accuracy improvement of Spot Vegetation S10.

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