胡顺石,黄春晓,杨斌,谭子芳

• 1:湖南师范大学资源与环境科学学院
• 2:湖南师范大学地理空间大数据挖掘与应用湖南省重点实验室

摘要(Abstract)：

针对多数植被指数序列重构方法不能有效去除连续云噪声的问题,该文提出了一种改进的自适应加权Savitzky-Golay滤波算法(IAW-SG)。以湖南省2001—2017年MOD13Q1植被指数产品归一化植被指数(NDVI)为数据源,通过解析质量控制参数,设置并在迭代过程中更新相应权重,自动调整滤波窗口大小以得到拟合结果,最终拟合曲线较为光滑,云噪声被有效消除;同时,该方法还被运用到MOD09Q1地表反射率产品得到的时间分辨率更高的NDVI序列产品,也可以得到较好拟合的效果。实验结果表明:该文算法拟合NDVI曲线能够较好地反映不同类型植被正常生长情况、年际变化规律等信息,同时还能最大限度保留原始序列有效值,可为生态环境监测提供高质量基础数据。该文算法通过植被指数产品质量控制参数实现权重和滤波窗口大小动态调整,具有较强的去噪能力,同时具有较强的数据保真性,能最大限度减少拟合误差。

关键词(KeyWords)： Savitzky-Golay(S-G)滤波;NDVI;时间序列;自适应加权;MODIS

Abstract:

Keywords:

基金项目(Foundation): 湖南省自然科学基金项目(2018JJ3348);; 湖南省教育厅科学研究项目(17C0952);; 中国国家留学基金项目(201806725009);; 湖南省地理学一流学科建设项目

作者(Author): 胡顺石,黄春晓,杨斌,谭子芳

DOI: 10.16251/j.cnki.1009-2307.2020.04.016

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