首页> 外文期刊>Frontiers of earth science >Reconstructing rice phenology curves with frequency-based analysis and multi-temporal NDVI in double-cropping area in Jiangsu, China
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Reconstructing rice phenology curves with frequency-based analysis and multi-temporal NDVI in double-cropping area in Jiangsu, China

机译:基于频率分析和多时相NDVI的江苏省双季稻水稻物候曲线重建

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Crop phenology retrieval in the double-cropping area of China is of great significance in crop yield estimation and water management under the influences of global change. In this study, rice phenology in Jiangsu Province, China was extracted from multi-temporal MODIS NDVI using frequency-based analysis. Pure MODIS pixels of rice were selected with the help of TM images. Discrete Fourier Transformation (DFT), Discrete Wavelet Transformation (DWT), and Empirical Mode Decomposition (EMD) were performed to decompose time series into components of different frequencies. Rice phenology in the double-cropping area is mainly located on the last 2 IMFs of EMD and the first 2aEuro'3 frequencies of DFT and DWT. Compared with DFT and DWT, EMD is limited to fewer frequencies. Multi-temporal MODIS NDVI data combined with frequency-based analysis can retrieve rice phenology dates with on average 79% valid estimates. The sorting result for effective estimations from different methods is DWT (85%)> EMD (80%)> DFT (74%). Planting date (88%) is easier to estimate than harvesting date (70%). Rice planting date is easily affected by the former cropping mode within the same year in a double-cropping region. This study sheds light on understanding crop phenology dynamics in the frequency domain of multi-temporal MODIS data.
机译:在全球变化的影响下,中国双季作物的作物物候检索对作物产量估算和水管理具有重要意义。在这项研究中,使用基于频率的分析从多时相MODIS NDVI中提取了中国江苏省的水稻物候。借助TM图像选择了水稻的纯MODIS像素。执行离散傅里叶变换(DFT),离散小波变换(DWT)和经验模态分解(EMD)将时间序列分解为不同频率的分量。双作区的水稻物候主要位于EMD的后2个IMF和DFT和DWT的前2aEuro'3频率。与DFT和DWT相比,EMD限于更少的频率。多时相MODIS NDVI数据与基于频率的分析相结合,可以检索到平均有效估计值为79%的水稻物候日期。通过不同方法进行有效估计的排序结果是DWT(85%)> EMD(80%)> DFT(74%)。播种日期(88%)比收获日期(70%)更容易估算。在同年种植双季稻的地区,水稻的播种日期很容易受到以前的种植方式的影响。这项研究为了解多时相MODIS数据频域中的作物物候动态提供了依据。

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