基于貝葉斯網(wǎng)絡模型的遙感圖像數(shù)據(jù)處理技術
A Processing Method For Remote sensing imagery data based on bayesian network model
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摘要: 貝葉斯網(wǎng)絡是一種不確定性知識的推理和描述技術,針對遙感數(shù)據(jù)的復雜性和不確定性,該文提出了一種基于貝葉斯網(wǎng)絡模型的遙感數(shù)據(jù)推理和描述技術。文中利用 2002年春季中-日亞洲沙塵暴項目的土地利用數(shù)據(jù)(LU),沙塵監(jiān)測數(shù)據(jù)(TSP),衛(wèi)星 AVHRR時間序列 LST/Albedo數(shù)據(jù),采用貝葉斯網(wǎng)絡模型進行了知識描述和信息推理預測實驗,取得了較好的效果。Abstract: Bayesian network is a new inference and express method of uncertain knowledge. It is proposed an inference and express technique for remote sensing imagery data which has complexity and uncertainty based on Bayesian Network Model(BNM). In the paper, the LU data, TSP and LST/Albedo data of AVHR.R time-sequence imagery which get from the project of China-Japan Asian dust storm in 2002 are used to analyze the dust storm and at the same time BNM is used to describe the knowledge and information inference. The satisfied results are given in the paper with the method.
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