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A crop phenology detection method using time-series MODIS data

机译：使用时序MODIS数据的作物物候检测方法

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Information of crop phenology is essential for evaluating crop productivity and crop management. Therefore we developed a new method for remotely determining phenological stages of paddy rice. The method consists of three procedures: (i) prescription of multi-temporal MODIS/Terra data; (ii) filtering time-series Enhanced Vegetation Index (EVI) data by time-frequency analysis; and (iii) specifying the phenological stages by detecting the maximum point, minimal point and inflection point from the smoothed EVI time profile. Applying this method to MODIS data, we determined the planting date, heading date, harvesting date, and growing period in 2002. And we validated the performance of the method against statistical data in 30 paddy fields. As for the filtering, we adopted wavelet and Fourier transforms. Three types of mother wavelet (Daubechies, Symlet and Coiflet) were used in Wavelet transform. As the results of validation, the wavelet transform performed better than the Fourier transform. Specifically, the case using Coiflet (order=4) gave remarkably good results in determining phenological stages and growing periods. The root mean square errors of the estimated phenological dates against the statistical data were: 12.1 days for planting date, 9.0 days for heading date, 10.6 days for harvesting date, and 11.0 days for growing period. The method using wavelet transform with Coiflet (order=4) allows the determination of regional characteristics of rice phenology. We proposed this new method using the wavelet transform; Wavelet based Filter for determining Crop Phenology (WFCP). (c) 2005 Elsevier Inc. All rights reserved.
机译：作物物候信息对于评估作物生产力和作物管理至关重要。因此，我们开发了一种用于远程确定水稻物候期的新方法。该方法包括三个程序：（i）规定多时间MODIS / Terra数据; （ii）通过时频分析过滤时间序列的增强植被指数（EVI）数据; （iii）通过从平滑的EVI时间曲线中检测最大点，最小点和拐点来指定物候阶段。将这种方法应用于MODIS数据，我们确定了2002年的播种日期，抽穗日期，收获日期和生长期。并针对30个稻田的统计数据验证了该方法的性能。至于滤波，我们采用了小波和傅立叶变换。小波变换使用了三种类型的母小波（Daubechies，Symlet和Coiflet）。作为验证的结果，小波变换的性能优于傅立叶变换。具体而言，使用Coiflet的情况（阶数= 4）在确定物候阶段和生长期方面给出了非常好的结果。估计物候日期与统计数据的均方根误差是：播种日期为12.1天，抽穗日期为9.0天，收获日期为10.6天，生育期为11.0天。使用带有Coiflet（阶数= 4）的小波变换的方法可以确定水稻物候的区域特征。我们使用小波变换提出了这种新方法。基于小波的滤波器，用于确定作物物候（WFCP）。 （c）2005 Elsevier Inc.保留所有权利。

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