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基于马尔可夫链和最大后验准则的模拟静止气象卫星数据地表组分温度反演

DOI: 10.3724/SP.J.1047.2013.00422, PP. 422-430

Keywords: 马尔可夫链,模拟,地表组分温度,静止气象卫星,最大后验准则

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Abstract:

地表组分温度比像元混合温度具有更强的物理意义和实用价值,是定量遥感反演的一个重要研究方向。本文以马尔可夫链和最大后验准则地表温度尺度转换方法,结合静止气象卫星数据高时间分辨率的特点,通过模拟静止气象卫星数据地表组分温度反演进行分析和验证。在研究过程中,地面被简化为由植被和土壤两组分组成,同时假设邻近像元的植被和土壤组分温度相同。鉴此,本文通过模拟构建20×20像元大小的静止气象卫星混合像元图像,并对各像元各时刻温度添加均值为0标准差为2K的随机误差,最终应用所提算法估算各像元各时刻的植被和土壤组分温度大小。精度分析结果表明,该算法能够较为精确地反演植被和土壤组分温度,且误差基本控制在2K以内。此外,本文还进一步讨论了算法的适用性及其对混合像元温度误差、植被覆盖度误差,以及邻近像元植被覆盖度变化范围的敏感度。分析结果再次证明,该方法对混合像元温度误差和植被覆盖度误差都具有较低的敏感性,在最大温度误差条件(均值为1.8K,标准差为5K)和最大植被覆盖度误差(均值为0.18,标准差为0.2)的条件下,各组分温度的估算精度分别能控制在3K和2K以内,满足精度要求。但是,由于组分温度初值的确定方法,对所计算窗口内植被覆盖度变化范围有较强的敏感性,反演结果与植被覆盖度变化范围相关,要求窗口内植被覆盖度变化范围足够大才能满足初值估算的精度要求。

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