## 1 Introduction  
Forests are important ecosystems that produce natural biological resources for humans [1, 2]. As a major terrestrial ecosystem, forests play essential roles in providing habitats for biomes, which maintain the global energy and material cycle, balancing greenhouse gas concentrations in the atmosphere and maintaining climate stability. Forest phenology is a key variable in conducting scientific management of forestry and has become important in climate change studies [3, 4]. Forest phenology refers to the sensitive reactions of forest vegetation biological events to seasonal variations in environmental variables such as temperature and humidity [5]. These reactions make forests the most sensitive indicator of environmental conditions [3,4]. The end of season (EOS) of broadleaf temperate deciduous forests of the eastern USA was widely delayed by 0.8 days per year from 1988 to 2008 [6]; an advanced trend was found at the start of season (SOS) of North American species [7], both clearly indicating the impact of global warming. Thus, accurate and detailed forest phenological measurements are essential not only for forestry management but also for climate change studies. Therefore, it is necessary to efficiently and economically monitor forest phenology. Observations of vegetation phenology have evolved over time. Traditional phenological observations are based on ground surveys and refer to human visual observations of the seasonal and annual variation in the biophysical dynamics of selected species [8]. The history of phenological ground surveys can be traced back to the observation of cherry blossoms in 705 AD in Japan [9], while Europe and the US have formed observation networks to record phenological information [10]. This method can provide accurate phenological information of specific species and is independent of instruments. However, the established observation networks can only cover a small localized area [8]. Furthermore, the standards for phenological records could be different, and records may contain biases due to times for budburst [6] or leaf opening [11] or to the amount of biomass [12]. Therefore, it is difficult to extend such observations to continental or global vegetation phenological studies. To overcome the limitation of ground surveys, remote sensing technologies have been utilized and both ground-based and satellite remote sensing approaches have been developed. Satellite remote sensing has the advantage of wider observational ranges and can be utilized in a broad range of applications. Common optical satellites such as NOAA, Terra, and Landsat can provide reliable observation data sources for phenological studies, along with some Synthetic Aperture Radar (SAR) measurements such as those obtained by the Sentinel-1 (S1) satellite [13, 14, 15]. Ground-based remote sensing can provide accurate site-level data but is restricted by the cost of instruments and frequency of the observations. However, these ground-based data can be used as references to evaluate the accuracy of satellite retrievals [12]. These methods can monitor vegetation over wider areas, longer time periods and can promote the development of phenological research. Therefore, remote sensing products have been widely used in recent studies. In phenological studies, passive optical remote sensing mainly focuses on microstructures of the vegetation such as chlorophyll which absorb red bands and leaf cells reflect near-infrared bands [16], while SAR products focus on the backscatter to determine the structure of leaves and branches [17]. The recently launched Sentinel-1 (S1) and Sentinel-2 (S2) satellites developed by the European Space Agency within the Copernicus Program have a 6-day and a 5-day repeat cycle respectively and have made a significant contribution in providing reliable surface remote sensing data with high spatial and temporal resolutions [15].