不同时序植被指数重构方法的江苏省冬小麦物候期提取的影响

发布时间：2018-05-22 07:24

本文选题：S-G滤波 + HANTS方法　；参考：《科学技术与工程》2017年25期

【摘要】：基于2009~2010年MODIS数据,以江苏省为研究区域,比较两种常见的重构植被指数序列方法的重构能力以及应用到冬小麦物候期提取上的效果;并且用观测数据对提取结果进行了验证。结果表明,两种重构方法都能较好的去除噪声,但Savitzky-Golay滤波方法在保持原始数据的真实性方面要优于HANTS(harmonic anazysis of time series)方法,而HANTS方法在呈现原始数据的周期性方面更有优势。通过动态阈值法提取冬小麦物候期时,经两种重构方法处理后的植被指数时间序列,在返青期和成熟期提取上均方根误差均在8 d之内,抽穗期效果较差。S-G滤波重构后的植被指数时间序列提取结果要优于HANTS方法。总体来说,经两种方法滤波后提取的江苏全省冬小麦关键物候期,都能够体现全省范围分布的变化性。
[Abstract]:Based on the MODIS data from 2009 to 2010, the reconstruction ability of two common reconstruction vegetation index sequence methods and their application to the phenological extraction of winter wheat were compared in Jiangsu Province, and the results were verified by observation data. The results show that both methods can remove noise, but the Savitzky-Golay filtering method is better than the HANTS(harmonic anazysis of time series) method in maintaining the authenticity of the original data, while the HANTS method has more advantages in presenting the periodicity of the original data. When the phenological period of winter wheat was extracted by dynamic threshold method, the mean square root error was within 8 days after two reconstruction methods. The result of time series extraction of vegetation index was better than that of HANTS method. In general, the key phenological periods of winter wheat extracted by two filtering methods in Jiangsu province can reflect the variation of the distribution of winter wheat in Jiangsu province.
【作者单位】：江苏省农业气象重点实验室;南京信息工程大学江苏省大气环境与装备技术协同创新中心;中国气象局气象探测中心;
【基金】：公益性行业(气象)科研专项(GYHY201506001) 吉林省气象局青年基金项目(2014006)资助
【分类号】：S162;S512.11

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