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作 者:李文 李佳田[1] 陆美 胡明洪 杨佳欣 LI Wen;LI Jiatian;LU Mei;HU Minghong;YANG Jiaxin(Faculty of Land Resource Engineering,Kunming University of Science and Technology,Kunming 650093,China)
机构地区:[1]昆明理工大学国土资源工程学院,昆明650093
出 处:《遥感信息》2023年第1期112-120,共9页Remote Sensing Information
摘 要:为准确重构受连续云雾污染NDVI时间序列,提高拟合曲线保真性,提出一种狄克松检验并融合时空信息的加权SG滤波法(SGDST)。首先,利用狄克松检验对像元生成一条标准参考曲线;其次,利用参考曲线和时空信息在目标像元邻域内找到相似像元,通过整合相似像元数据生成预处理序列;最后,通过加权SG滤波法对处理后NDVI序列进行平滑,获得高质量NDVI时序数据。采用2010—2019年MODS13Q1_NDVI数据,与SG滤波法、DL拟合法和AG法对比。结果表明:在拟合曲线时,SGDST方法能准确重构连续多期缺失数据的时间序列,有效保留局部波峰波谷细节特征;处理顽固噪声时,可避免过度修正有效低值;与其他3种方法相比,SGDST法的均方根误差和绝对平均误差小于0.0853像元,占拟合总像元比例最大,保真度最高。In order to accurately reconstruct the NDVI time series polluted by continuous clouds and fog and to improve the fidelity of the fitted curve,this paper proposes a weighted SG filtering method based on the Dixon test and the fusion of spatiotemporal information.Firstly,use the Dixon test to generate a standard reference curve for the pixel.Secondly,the reference curve and spatiotemporal information are used to find similar pixels near the target pixel,and the preprocessing sequence is generated by integrating similar pixel data.Finally,the processed NDVI sequence is smoothed by the weighted SG filtering method to obtain high-quality NDVI time series data.MODS13Q1_NDVI data from 2010-2019 were used for comparison with the SG filter method,the double logistic fitting method,and the asymmetric Gaussian function method.The results show that when fitting the curve,the SGDST method can accurately reconstruct the time series of missing data for multiple consecutive periods,and effectively retain the details of local peaks and troughs;when there is noise,it can avoid over-correcting the effective low value.Compared with the other three methods,the SGDST method has the largest proportion of root mean square error and mean absolute error which are less than 0.0853 pixels in the total fitted pixels and the best fidelity.
关 键 词:MODIS NDVI 拟合重建 加权SG滤波 狄克松检验 时空信息融合
分 类 号:TP751[自动化与计算机技术—检测技术与自动化装置]
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