## 2 Methods for Monitoring Phenology  
Phenological monitoring methods can be classified into three types based on the spatial coverage of monitoring as follows: the species level, plot-regional level, and regional-global level (Figure 1). A human observer has traditionally monitored individual organisms to visually document changes in forest phenological parameters [2]. This method of collecting plant phenological data is known for its long temporal resolutions, enabling the availability of data from the 1900s in multiple locations worldwide [19]. However, it is worth noting that the spatial distribution of these data is currently limited to a few countries, primarily including the USA (National Phenology Network, Budburst, and National Ecological Observatory Network), Canada (Nature Watch), Sweden (Swedish National Phenology Network), Russia (Chronicles of Nature), Australia (Climate Watch), Pan European Phenology database (PEP725) and the UK (Nature's Calendar). Despite these efforts, ground-based phenological observations face certain limitations, such as being constrained to a limited number of species, being more prone to human errors, requiring significant labor, and being time-consuming [20; 21]. Figure 1: Overview of different methods of phenological monitoring. (Individual level: PL: production of young leaves, ML: maturation of leaves, AL: abscission of leaves, PF: production of young flowers, MF: maturation of flowers, AF: abscission of flowers, Pfu: production of young fruits, Mfu: maturation of fruits, Rfu: ripening of fruits; plot-regional level: SOS: start of season, EOS: end of season, LOS: length of season, LE: leaf expansion, FA: flower appearance, LC: leaf coloring, LF: leaf fall). Since the 1970s, satellite-based remote sensing has introduced new possibilities for worldwide phenological surveillance at the landscape scale with the advantage of continuously collecting data for large areas. Land surface phenology (LSP) is the term generally used to represent vegetation phenology derived using satellite-based remote sensing estimated from vegetation indices (VI) or biophysical variables [22; 23]. Multiple studies have confirmed the shift in phenological timing at a regional and global scale due to a shift in climatic conditions, such as changes in precipitation, temperature patterns, and a shift in snowfall timings [4; 7]. Using satellite data, the phenological study at a global scale has confirmed a significant advancement in the SOS by 0.38 days per year, a delay in the EOS by 0.45 days per year, and a global increase in the LOS by 0.8 days per year [24]. Similarly, several studies have also reported a shifting phenological period at the regional and continental levels [10; 22]. However, the practical application of satellite-based remote sensing in phenological monitoring faces several constraints, including low temporal and spatial resolution, susceptibility to cloud cover, and the modifiable area unit problem (MAUP), where the pixel being monitored may not correspond precisely to the ground location at different times [25; 26; 27]. Additionally, while comparing ground observations and satellite-based monitoring, the major difference is the footprint mismatch. Ground observations record phenology at the individual species level, which makes it difficult to compare it with a satellite-based phenological product at the regional scale. This pronounced disparity in footprint size underscores the need for near-surface monitoring techniques that are capable of capturing phenological data at the plot level. It is interesting to note that the first fully digital camera came into existence after a decade of the first operational earth observation satellite.