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干旱区绿洲典型地物MESMA模拟分解与验证

DOI: 10.3724/SP.J.1047.2013.00452, PP. 452-460

Keywords: 多端元光谱混合分析,最小平均波谱角,遥感,混合像元

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Abstract:

混合像元作为遥感信息的不确定性,一直是定量遥感科学研究的核心领域之一,干旱区由于下垫面均匀、气象条件单一等先天条件,已成为定量遥感产品真实性检验的理想场所。本文以塔里木盆地北缘的库车河绿洲为研究区,首先,针对不同地物类型分别采用不同方法进行地物端元提取;然后,以端元均方根EAR(EndmemberAverageRMSE,EAR)和最小平均波谱角(MinimumAverageSpectralAngle,MASA)值来选取最优端元;最后,用多端元光谱混合分析(MultipleEndmemberSpectralMixtureAnalysis,MESMA)模型进行光谱混合分解,并对结果作了精度评价与比较分析。结果表明MESMA模型能有效提高像元内基本组分丰度信息精度,从而为典型地物高精度提取提供了科学方法。

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