## 2 Global Open Earth Observations Satellite Missions for Monitoring Land Surface Phenology
### Moderate Resolution Imaging Spectroradiometer (MODIS)
Earlier greening trends in China for the period 2000-2020 are detected on 25% of vegetated land and earlier browning on 11% [48]. The derived vegetation condition index (VCI) during 2001-2020 [49] showed an upward trend of vegetation activity in 90.63% of regions in China, while a downward trend is present in 9.37% of the areas. This was confirmed by [PERSON] [50], who obtained the increasing NDVI and EVI trends for the study region of the Qinling-Daba Mountains. Variations in the SOS are closely related to the snow cover, particularly the earlier end of snow cover, which caused earlier greening in the studied mountain region across all elevations [51]. However, the snow cover duration is positively correlated with the length of the growing season, which could be explained through improved soil water availability in the following season. Analyzed responses of vegetation using NDVI for the period 2000-2020 over Inner Mongolia [52] showed that typical steppes demonstrated the highest sensitivity to precipitation, followed by desert steppes, forest steppes, broad-leaved forests, deserts, and coniferous forests. MODIS datasets have also been transformed into products that more closely represent the physiological status of vegetation, their photosynthesis, and energy fluxes, which are strongly related to primary production. One of such products represents solar-induced chlorophyll fluorescence (SIF), which is derived from MODIS enhanced vegetation index (EVI) and meteorological reanalysis data (air temperature, vapor pressure deficit, short-wave solar radiation). Indices such as SIF enable analysis of the relationship of climatic factors on vegetation processes related to the phenology and vegetation photosynthetic activity that is performed by [PERSON] et al. [53] over subtropical China. By using the above indices and relationships, they concluded that vegetation photosynthesis, as indicated by SIF, showed an increasing trend over the majority of the study area. Soil moisture primarily exhibits lag effects on the vegetation activity in all studied forest types (evergreen coniferous, deciduous broadleaf, and mixed forests), where temperature does not exhibit significant temporal effects. The spatio-temporal variations in the SOS are mainly influenced by both spring temperature and winter precipitation, with increasing precipitation in winter tending to delay the SOS, while increasing spring temperature tended to advance the SOS [54]. This can be explained by the fact that spring temperature is closely linked to the heat accumulation of plants, while winter precipitation indirectly affects the temperature in spring and therefore also causes a delay in SOS. Also, there is a very wide range of other studies in China that use MODIS-derived time series indices and various methodological approaches on a regional and local scale that more or less observe the general pattern in vegetation dynamics under the impact of climatic variables and factors [55; 56; 57; 58]. Snow cover duration in arid montane areas of Central Asia has the most influence on the peak height of seasonal vegetation patterns (the maximum modeled NDVI) [59]. Phenological pattern in terms of the accumulated growing degree-days (AGDD) from MODIS 8-day compositesof land surface temperatures can also be inversely applied for characterization of the land cover/land use classes, which was an approach suggested by [PERSON] et al. (2018). Due to its high temporal resolution, MODIS is often used as a proxy for monitoring or scaling of the terrestrial biological productivity, which is important for assessment and modeling of the carbon cycle. Land surface phenology, which records the start of growing season (SOS) and the end of growing season (EOS), presents a proxy indicator that reflects plant photosynthesis and the response of the carbon cycle in terrestrial ecosystems to climate change ([PERSON] et al., 2018).