## 2 Global Open Earth Observations Satellite Missions for Monitoring Land Surface Phenology
### Moderate Resolution Imaging Spectroradiometer (MODIS)  
MODIS performs imaging of the Earth's surface with a total of 36 spectral channels reflecting different purposes: land, clouds, aerosols, ocean color, phytoplankton, atmospheric water vapor, surface temperature, cloud temperature, atmospheric temperature, ozone, and cloud top altitude. MODIS has variable spatial resolution, i.e., bands of 250 m, 500 m, and 1000 m, and derived products at daily, 4-day, 8-day, monthly, quarterly, and yearly temporal resolution. The medium-resolution MODIS dataset enables a better breakdown and analysis of the LSP signature depending on different land cover categories or vegetation types. The influence of mixtures of the reflectance signal from different land surfaces, which is present in AVHRR, can be reduced, to a large extent, by using medium spatial resolution satellites, and clean feedback can be extracted from relatively homogeneous land categories. Although the temporal frame in which continuous observations of the Earth's surface are carried out is almost twice as short with MODIS (from 2000 to the present), a period of almost 2.5 decades is long enough to observe changes in LSP on a regional or global level. Global coverage of MODIS data enables the analysis of vegetation trends or LSP due to the effect of climate change on a global scale. Phenology changes due to the climate warming in the Northern Hemisphere, analyzed by [PERSON] et al. [40]. The conducted research determined that the vegetation activity, expressed through the index as solar-induced chlorophyll fluorescence (SIF), gross primary productivity (GPP), and net primary productivity (NPP), has increased in 72.01% to 88.04% of the vegetation areas. Increased productivity is related to the early spring phenology, delayed autumn phenology, extended growing season length, increased soil moisture, and elevated temperature. LSP derived from the MODIS time series data enables precise analysis of the controls of various climatic factors on vegetation dynamics. Climate forcings on the spring green-up were studied in North American deciduous forests by [PERSON] et al. [41], who concluded that photoperiod dominantly controls leaf emergence in warmer climates but exerts only modest influence in colder climates where temperature shows a more distinctive role. A study performed in Central Europe [42] analyzed green-up duration of deciduous broadleaf forests, which is mainly positively influenced by the start of green-up (SOS), and concluded that benefits of climate change, possibly realized as a longer growing season, could be smaller than anticipated. Studies concerning LSP phenometrics using medium-resolution MODIS time series provide some clues about differences in vegetation dynamics that are closely related to the specific regional climatic properties (temperature and precipitation patterns) and the altitudinal gradient. MODIS-derived LSP over the Iberian Peninsula [43] shows that SOS and EOS dates generally occurred later in the Alpine and Atlantic biogeographic regions, while earlier in the Mediterranean. The study performed in southern China shows that the relationship between preseason average temperature, precipitation, and SOS is more evident in higher altitude areas [44]. Preseason average temperature also influences an earlier withering and yellowing of vegetation and consequently earlier EOS. The study of [PERSON] et al. [45] discloses seasonal phenological patterns of major land cover types over different sub-regions in Africa with 500 m spatial resolution. The influence of daily temperature and precipitation on NDVI vegetation dynamics in Nigeria was examined using a statistical downscaling modelling approach [46]. Comparing NDVI trends during 2000-2020 in the Yellow River Basin in China [47] provides a general regional declining pattern from northwest to southeast, with positive effects of deep leached soils with high organic matter and weak water erosion. Vegetation growth is decreased in cities with strong human activities.