植被物候是指示植被对自然环境变化响应的重要指标。大兴安岭多年冻土区是我国唯一的高纬度多年冻土区，该区植被物候的研究有助于认识寒区生态系统对全球气候变化的响应。本文首先比较了归一化植被指数（NDVI）、增强型植被指数（EVI）和日光诱导叶绿素荧光（SIF）在多年冻土区物候研究中的差异和适应性，结果表明EVI的应用效果最佳。其次，结合2000—2019年MODIS EVI时间序列数据和气象数据，采用Savitzky-Golay（S-G）滤波和动态阈值等方法提取植被生长季开始（SOS）、结束（EOS）和长度（LOS）等关键物候参数，分析大兴安岭多年冻土区植被物候的时空变化及其对气候变化的响应。结果表明：（1）NDVI、EVI和SIF的时间序列均能反映研究区植被生长的季节变化，与NDVI相比，EVI与SIF的变化曲线更加一致。（2）研究区2000—2019年SOS变化范围为年序日96~144 d，平均值为129.46 d。EOS变化范围为272~320 d，平均值为295 d。LOS集中分布在128~224 d，平均值为165.65 d。由于植被类型差异和逆温现象的存在，大片连续多年冻土区的LOS大于岛状融区多年冻土区。（3）研究区SOS和EOS变化趋势的平均值分别为-1.23 d·（20a）^-1和-0.46 d·（20a）^-1，均呈提前趋势。LOS变化趋势的平均值为2.39 d·（20a）^-1，呈延长趋势。研究区植被SOS与3—5月平均气温呈显著负相关，EOS与8—10月平均气温和降水呈显著正相关。

Vegetation phenology is an important indicator of vegetation response to changes of the natural environment. As an important component of the cryosphere， permafrost is extremely sensitive to climate change. Accurate monitoring of vegetation phenology in permafrost areas is important for studying the response of cold-zone ecosystems to climate change. The Greater Khingan Mountains permafrost zone is the only high-latitude perennial permafrost in China， and studying the vegetation phenology in this zone can improve our understanding the response of cold-zone ecosystems to global climate changes. In order to investigate the impact of climate change on vegetation in the permafrost zone of the Greater Khingan Mountains， this paper assesses the spatial and temporal characteristics of vegetation phenology in the study area over the past 20 years and its response to climate change based on MODIS EVI time series data， with a view to enriching the study of vegetation phenology in cold-zone ecosystems. This study firstly compares the differences and adaptability of Normalized Difference Vegetation Index （NDVI）， Enhanced Vegetation Index （EVI） and Solar-induced Chlorophyll Fluorescence （SIF） in phenology studies of the permafrost zone， and the results show that EVI is more effective than the other two indices. Secondly， combines MODIS EVI time series data and meteorological data from 2000 to 2019， key phenological parameters， the beginning （SOS）， end （EOS） and length （LOS） of vegetation growing season， were extracted using Savitzky-Golay （S-G） filter and dynamic threshold approaches to analyze the spatial and temporal variation of vegetation phenology in the study region and its response to climate changes. In this case， the NDVI and EVI have a spatial resolution of 250 m and a temporal resolution of 16 d. Data processes such as mosaicking， masking and projection transformations were performed on each period of data to obtain time series data of NDVI and EVI for the study area from 2000 to 2019. The 16 d of SIF data were combined into one period according to MODIS data synthesis rules， with 23 periods of data per year. And the mean value of SIF for the study area was calculated to obtain time series data for SIF from 2015 to 2019. Monthly mean temperature and monthly total precipitation in growing seasons were selected and used the method of partial correlations analysis to analyze how climate factors affect vegetation phenology. The results show that： （1） the time series of NDVI， EVI and SIF can reflect the seasonal changes of vegetation growth in the study area， and the change curves of EVI and SIF are more consistent than those of NDVI； （2） the variation of SOS in the study area from 2000 to 2019 ranged from 96 to 144 d in chronological days， with a mean value of 129.46 d； the variation of EOS ranged from 272 to 320 d， with a mean value of 295 d and the LOS was concentrated between 128 and 224 d， with a mean value of 165.65 d. Due to the existence of the inversion phenomenon and the differences of vegetation types， the LOS in the continuous multi-year permafrost area was greater than that in the island thaw zone； （3） the mean values of SOS and EOS trends in the study area were -1.23 d·（20a）^-1 and -0.46 d·（20a）^-1， respectively， both showing early trends and the mean value of LOS trend was 2.39 d·（20a）^-1， showing an extended trend. Vegetation SOS in the study area was negatively correlated with the mean temperature of March to May （P<0.05）， and EOS was positively correlated with the mean temperature and precipitation August to October （P<0.05）. The extent and trend of significant changes in vegetation phenology were greater in the continuous permafrost zone than that in the island thaw zone permafrost zone， indicating that continuous permafrost zone is more sensitive to climate change. This research improve our understanding of vegetation phenology characteristics of permafrost region under the background of climate change.