Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), extracted from the Moderate Resolution Imaging Spectrometer (MODIS), are widely used to monitor phenology by calculating land surface reflectance. However, the applicability of the vegetation index based on ‘greenness’ to monitor photosynthetic activity is hindered by poor observation conditions (e.g., ground shadows, snow, and clouds). Recently, satellite measurements of solar-induced chlorophyll fluorescence (SIF) from OCO-2 sensors have shown great potential for studying vegetation phenology. Here, we tested the feasibility of SIF in extracting phenological metrics in permafrost regions of the northeastern China, exploring the characteristics of SIF in the study of vegetation phenology and the differences between NDVI and EVI. The results show that NDVI has obvious SOS advance and EOS lag, and EVI is closer to SIF. The growing season length based on SIF is often the shortest, while it can represent the true phenology of vegetation because it is closely related to photosynthesis. SIF is more sensitive than the traditional remote sensing indices in monitoring seasonal changes in vegetation phenology and can compensate for the shortcomings of traditional vegetation indices. We also used the time series data of MODIS NDVI and EVI to extract phenological metrics in different permafrost regions. The results show that the length of growing season of vegetation in predominantly continuous permafrost (zone I) is longer than in permafrost with isolated taliks (zone II). Our results have certain significance for understanding the response of ecosystems in cold regions to global climate change.

植被物候是指示植被对自然环境变化的反应的指标，对于研究全球气候变化及其对陆地生态系统的影响具有重要意义。从中分辨率成像光谱仪（MODIS）中提取的归一化植被指数（NDVI）和增强植被指数（EVI）被广泛用于通过计算土地表面反射率来监测物候。然而，由于恶劣的观测条件（例如，地面阴影，雪和云），阻碍了基于“绿色”来监测光合作用活动的植被指数的适用性。最近，卫星对来自OCO-2传感器的太阳诱导的叶绿素荧光（SIF）的测量显示出了研究植物物候的巨大潜力。这里，我们测试了SIF提取东北多年冻土地区物候指标的可行性，探讨了SIF在植被物候学研究中的特征以及NDVI和EVI之间的差异。结果表明，NDVI具有明显的SOS提前和EOS滞后，EVI更接近SIF。基于SIF的生长期通常最短，因为它与光合作用密切相关，因此可以代表植被的真实物候。在监测植被物候的季节性变化时，SIF比传统的遥感指数更敏感，并且可以弥补传统植被指数的不足。我们还使用MODIS NDVI和EVI的时间序列数据来提取不同多年冻土地区的物候指标。结果表明，主要是连续多年冻土区（I区）的植被生长季节的长度要长于孤立的塔利木（II区）中的植被的生长季节的长度。我们的结果对于了解寒冷地区生态系统对全球气候变化的响应具有一定意义。