期刊
INTERNATIONAL JOURNAL OF REMOTE SENSING
卷 32, 期 17, 页码 4769-4785出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/01431161.2010.489067
关键词
-
资金
- National Science & Technology Pillar Program of China [2008BAK49B07]
- National Natural Science Foundation of China [40901208, 40901211]
- MODIS Satellite Data Reception Station at Wuhan University
A new algorithm is presented for land-fog detection using daytime imagery from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data. MODIS images constitute an ideal data source for fog detection due to their outstanding spatial and spectral resolution. In this article, a parameter named the Normalized Difference Fog Index (NDFI) is proposed, based on analysing the spectral character of fog and cloud by utilizing the Streamer radiativetransfer model and MODIS data. A mean-shift segmentation method is used to preliminary segment the NDFI image, and a full lambda-schedule algorithm is then iteratively applied to merge adjacent segments based on the combination of spectral and spatial information. Then, some properties (e. g. mean value of brightness temperature) are calculated for each segment, and each object is identified as either fog or not. The algorithm's performance is evaluated against ground-based measurements over China in winter, and the algorithm is proved to be effective in detecting fog accurately based on three cases.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据