首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Derivation of phenological metrics by function fitting to time-series of Spectral Shape Indexes AS1 and AS2: Mapping cotton phenological stages using MODIS time series
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Derivation of phenological metrics by function fitting to time-series of Spectral Shape Indexes AS1 and AS2: Mapping cotton phenological stages using MODIS time series

机译:通过函数拟合光谱形状指数AS1和AS2的时间序列来推导物候指标:使用MODIS时间序列映射棉花物候阶段

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The availability of high frequency remote sensing time series allows the assessment of crop evolution at different scales. The Spectral Shape Indexes (SSI) represent the shape of a multispectral (MODIS in this case) reflectance profile in a set of three consecutive bands.The aims of this research were: (1) to assess AS1 and AS2 behavior over a cotton crop growing period, (2) to test whether function fitting procedures can be used to model MODIS AS1 and AS2 and NDVI time series and (3) to derive objective AS1 and AS2 phenological metrics that can be used to monitor cotton phenological stages.Phenological stages of a cotton crop in the San Joaquin Valley (CA) were identified by linking local climatic data and producer recorded management practices. An asymmetric Gaussian function was fitted to the time series of each index using TIMESAT software. Then, specific dates in the fitted functions have been related to phenological stages and dates of agricultural practices.Results show that AS1 and AS2 exhibit a consistent pattern clearly different from the temporal evolution of NDVI. The AS2 index shows high values during periods when vegetation is dominant, either photosynthetically active or dry, and low values when soil dominates the pixel. The AS1 index time series showed two minima during the cotton growth period. Minima and inflection points derived from the fitted functions are coincident in time with significant crop management dates during the growing period. These results show that function fitting procedures applied to AS1 and AS2 can be used to derive phenological metrics, illustrating the potential for using Spectral Shape Indexes for crop monitoring.
机译:高频遥感时间序列的可用性允许评估不同规模的作物进化。光谱形状指数(SSI)代表三个连续波段中一组的多光谱反射率曲线的形状。本研究的目的是:(1)评估棉花作物上AS1和AS2的行为期间,(2)测试功能拟合程序是否可用于对MODIS AS1和AS2和NDVI时间序列建模,以及(3)得出可用于监测棉花物候阶段的客观AS1和AS2物候指标。通过将当地气候数据与生产者记录的管理实践联系起来,确定了圣华金谷(CA)的棉花作物。使用TIMESAT软件将不对称高斯函数拟合到每个索引的时间序列。然后,拟合函数中的特定日期与物候阶段和农业实践的日期有关。结果表明,AS1和AS2呈现出与NDVI的时间演变明显不同的一致模式。在植被占主导地位(光合作用或干旱)期间,AS2指数显示较高的值,而在土壤占主导地位的像素期间,AS2指数显示较低的值。 AS1指数时间序列显示了棉花生育期的两个最小值。从拟合函数得出的最小值和拐点在生长期间的时间上与重要的作物管理日期一致。这些结果表明,应用于AS1和AS2的函数拟合过程可用于导出物候指标,从而说明了使用光谱形状指数进行作物监测的潜力。

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