【摘要】 植被物候是表征生态系统对气候变化响应的重要指标。草地枯黄期是研究陆地生态系统对气候变化响应的重要指标，然而，植被枯黄期研究较少，寻找适合提取当地的植被枯黄期的最佳模型显得尤为重要。本研究采用双逻辑斯蒂函数拟合法(D-L)、非对称性高斯函数拟合法(A-G)、Savitzky-Golay滤波法(S-G) 3种方法分别模拟了2001-2019年新疆地区草地枯黄期，对比草地枯黄期不同物候提取方法，确定新疆地区草地枯黄期的最佳遥感提取方法，并对草地枯黄期空间格局及变化趋势进行分析。结果表明：1)双逻辑斯蒂函数拟合法是提取新疆地区枯黄期的最佳方法。2) 3种方法估算的新疆地区草地枯黄期均呈现自北向南逐渐提前的明显地域差异。3) 3种遥感方法估算的草地枯黄期均呈现提前的趋势，显著提前(P <0.1)的区域分布于阿尔泰山以南、准噶尔盆地中部及西部边缘区。4)不同草地类型下，利用A-G和D-L两种方法提取的草地枯黄期年际变化趋势基本保持一致。更多还原

【Abstract】 The pros and cons of vegetation phenology reconstruction and extraction methods for different regions still need to be fully elucidated. Therefore, performing a comparative analysis between different methods is necessary to achieve optimal remote sensing extraction in a specific region. In this study, the asymmetric Gaussian function fitting(Asymmetric Gaussian,AG), double logistic function fitting(Double Logistic, DL), and Savitzky-Golay filter(SG) methods were used to extract the end of season(EOS) data for grasslands in Xinjiang from 2001 to 2019. By comparing the extraction results of four methods,an optimal model suitable for extracting EOS was established and the temporal and spatial changes in the EOS data were studied in Xinjiang. The main conclusions of this study were as follows: 1) The SOS results for Xinjiang grassland extracted using the D-L method were the best. 2) The grassland area in Xinjiang estimated using the three methods showed distinct regional differences; EOS gradually advanced from north to south. 3) The grassland EOS estimated using all three methods showed an advancing trend, and the areas where EOS advanced significantly(P < 0.1) are distributed in the area south of the Altai Mountains and in the central and western marginal areas of the Junggar Basin. 4) The annual variation trend of grassland phenology extracted using A-G and D-L was consistent for all the studied grassland types.更多还原