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谌稳1,2, 孙立群1,*, 李晴岚1, 陈晨3, 李家叶3
收稿日期:
2021-04-06
修回日期:
2021-07-06
作者简介:
谌稳(1996—),男,硕士生,湖南怀化人,主要从事气象相关方面研究。E-mail: 201821511214@smail.xtu.edu.cn
基金资助:
CHENWen1,2, SUN Liqun1,*, LI Qinglan1, CHEN Chen3, LI Jiaye3
Received:
2021-04-06
Revised:
2021-07-06
Supported by:
摘要: MODIS的增强型植被指数(EVI)时间序列数据早已广泛应用于植被观测、生态环境和全球气象变化等研究领域,但即使EVI时间序列数据已经经过严格的预处理,其中仍然存在着一些噪声。因此,本文开发了一种简单有效的方法来重构EVI时间序列数据,减少EVI 时间序列数据中的噪声,尤其是一些由大气云层和冰雪覆盖产生的噪声。新方法的理论来源于图论,利用拉普拉斯矩阵的关系对EVI中选定的邻域窗口的像元权重进行赋值,得到中心像元的拟合。新方法已应用于2016—2018 年的MODIS MOD13A1 产品,并与S-G滤波法、谐波函数法、双逻辑斯蒂拟合法和非对称高斯函数法进行了比较。结果表明,在荒漠、草原和林地中,新方法留一验证测试的绝对差值最小,相较于其他方法效果较优;在拟合不同植被类型的EVI时间序列数据时,图论邻点方法呈现出更好的细节拟合曲线;其在5 类植被类型中的RMSE 值分别为200.59、46.58、63.48、165.47 和40.95,在5 种方法中均为最小值,在获取高保真和高质量的EVI时间序列数据方面优势更明显有效。本文的方法研究可以给植被遥感时序数据的去噪和生态环境的研究提供有益借鉴。
谌稳, 孙立群, 李晴岚, 陈晨, 李家叶. 一种基于图论重构MODIS EVI时间序列数据集的新方法[J]. 地球信息科学学报, , (): 1-2.
CHENWen, SUN Liqun, LI Qinglan, CHEN Chen, LI Jiaye. A New Method to Reconstruct MODIS EVI Time Series Data Set based on Graph Theory[J]. Journal of Geo-information Science, , (): 1-2.
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