ABSTRACT The temporal resolution of vegetation indices (VIs) determines the details of seasonal variation in vegetation dynamics observed by remote sensing, but little has been known about how the temporal resolution of VIs affects the retrieval of land surface phenology (LSP) of grasslands. This study evaluated the impact of temporal resolution of MODIS NDVI, EVI, and per-pixel green chromatic coordinate (GCCpp) on the quality and accuracy of the estimated LSP metrics of prairie grasslands. The near-surface PheonoCam phenology data for grasslands centered over Lethbridge PhenoCam grassland site were used as the validation datasets due to the lack of in situ observations for grasslands in the Prairie Ecozone. MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data from 2001 to 2017 were used to compute the time series of daily reference and to simulate 2–32 day MODIS VIs. The daily reference and simulated multi-day time series were fitted with the double logistic model, and the LSP metrics were then retrieved from the modeled daily time series separately. Comparison within satellite-based estimates showed no significant difference in the phenological metrics derived from daily reference and multi-day VIs resampled at a time step less than 18 days. Moreover, a significant decline in the ability of multi-day VIs to predict detailed temporal dynamics of daily reference VIs was revealed as the temporal resolution increased. Besides, there were a variety of trends for the onset of phenological transitions as the temporal resolution of VIs changed from 1 to 32 days. Comparison with PhenoCam phenology data presented small and insignificant differences in the mean bias error (MBE) and the mean absolute error (MAE) of grassland phenological metrics derived from daily, 8-, 10-, 14-, and 16-day MODIS VIs. Overall, this study suggested that the MODIS VIs resampled at a time step less than 18 days are favorable for the detection of grassland phenological transitions and detailed seasonal dynamics in the Prairie Ecozone.

中文翻译：

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调查 MODIS 数据的时间分辨率对草原草原物候测量的影响

摘要 植被指数 (VIs) 的时间分辨率决定了遥感观测到的植被动态季节性变化的细节，但关于 VIs 的时间分辨率如何影响草地地表物候 (LSP) 的反演知之甚少。本研究评估了 MODIS NDVI、EVI 和每像素绿色色度坐标 (GCCpp) 的时间分辨率对草原草原 LSP 指标估计质量和准确性的影响。由于缺乏对草原生态区草地的原位观测，以 Lethbridge PhenoCam 草地站点为中心的草地的近地表 PheonoCam 物候数据被用作验证数据集。MODIS 天底双向反射分布函数 (BRDF)-调整反射 (NBAR) 数据从 2001 年到 2017 年用于计算每日参考的时间序列并模拟 2-32 天 MODIS VI。每日参考和模拟的多日时间序列采用双逻辑模型进行拟合，然后分别从建模的每日时间序列中检索 LSP 指标。基于卫星的估计中的比较表明，来自每日参考和多天 VI 的物候指标没有显着差异，时间步长小于 18 天。此外，随着时间分辨率的增加，多天 VI 预测每日参考 VI 的详细时间动态的能力显着下降。除了，随着 VI 的时间分辨率从 1 天变为 32 天，物候转变的开始有多种趋势。与 PhenoCam 物候数据的比较表明，来自每日、8、10、14 和 16 天 MODIS VI 的草地物候指标的平均偏差误差 (MBE) 和平均绝对误差 (MAE) 存在微小且不显着的差异。总体而言，这项研究表明，在不到 18 天的时间步长内重新采样的 MODIS VI 有利于检测草原生态区的草原物候转变和详细的季节动态。和 16 天 MODIS VI。总体而言，这项研究表明，在不到 18 天的时间步长内重新采样的 MODIS VI 有利于检测草原生态区的草原物候转变和详细的季节动态。和 16 天 MODIS VI。总体而言，这项研究表明，在不到 18 天的时间步长内重新采样的 MODIS VI 有利于检测草原生态区的草原物候转变和详细的季节动态。