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.