Abstract：
Phenology has been useful to better understand the climate-vegetation relationship, and it is considered an indicator of climate change impact. Phenological data have been generated through multiple remote sensing techniques and ground-based observations through professional or citizen science. The combination of both techniques is known as cross-scale phenological monitoring. However, no comparative analysis has been carried out to assess the advantages and disadvantages of each of these techniques to characterize the phenological cycle of forest ecosystem species. This work is a content-analysis-based review of scientific literature published between 2000 and 2018 related to cross-scale monitoring methods, to estimate the phenological variation in different forest ecosystems worldwide. For this study, 97 publications related to cross-scale phenological monitoring were selected. We found that 71% of the articles aimed to corroborate the data generated through satellite imagery using surface data from either phenocams, flux towers, or from citizen science networks. More publications were published by authors in the USA (30%), Canada (8%), and China (7%). The most commonly used vegetation index was the normalized difference vegetation index (65%). Some deficiencies in the evaluation of the phenological phases of autumn when compared with surface observations were found. Flux towers and phenocams were included as alternatives for ground-based monitoring. Cross-scale phenological monitoring has the potential to characterize the phenological response of vegetation accurately due to data combinations at two different observation scales. This work contributes to specifying the methodologies used in gathering phenological parameters of the world\'s forest ecosystems.
摘要：
物候学有助于更好地理解气候-植被关系，它被认为是气候变化影响的指标。物候数据是通过多种遥感技术和通过专业或公民科学进行的地面观测产生的。两种技术的组合被称为跨尺度物候监测。然而,没有进行比较分析来评估每种技术的优缺点，以表征森林生态系统物种的物候周期。这项工作是对2000年至2018年之间发表的与跨尺度监测方法有关的科学文献的基于内容分析的综述，估计全球不同森林生态系统的物候变异。对于这项研究，选择了97份与跨尺度物候监测有关的出版物。我们发现，71%的文章旨在使用来自任一现象的地表数据来证实通过卫星图像生成的数据，通量塔,或者来自公民科学网络。更多的出版物是由作者在美国（30％），加拿大（8%）和中国（7%）。最常用的植被指数是归一化差异植被指数(65%)。与地表观测相比，发现秋季物候阶段的评估存在一些不足。包括通量塔和phenocams作为地面监测的替代方案。由于两种不同观测尺度下的数据组合，跨尺度物候监测具有准确表征植被物候响应的潜力。这项工作有助于指定用于收集世界森林生态系统物候参数的方法。
