This study evaluates the performances of three global satellite datasets (Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Satellite pour l’ observation de la Terre (SPOT) of the Mongolian Plateau, where in situ observation is insufficient to assess vegetation dynamics on terrestrial systems. We give a comprehensive assessment of the historical changes in vegetation dynamics by using comparative and correlation methods on the three archives using two indices: the growing season’s Normalized Difference Vegetation Index (NDVI) and the Start of the Season Index (SOS). The main findings are: (1) MODIS and SPOT have generally better comparability and consistency in the spatial-temporal trends of NDVI and SOS than AVHRR in this area; (2) all the three archives exhibit better consistency in Inner Mongolia than in Mongolia; (3) integration data analysis of AVHRR (1982–1997) and SPOT (1998–2012) shows that the dynamics of vegetation growth has three distinct phases: enhanced before 1994; a flatter/slightly decreasing trend before 2001; and, then, a rapid recovery between 2001 and 2012 with remarkable spatial heterogeneity, with Inner Mongolia experiencing a significant greening in vegetation NDVI compared with no obvious changes in Mongolia; (4) the temporal average SOS showed no significant “earlier spring” onset during the past 31 years, on the middle and northern Mongolian Plateau. Full article

Using estimated leaf unfolding data and two types of Normalized Difference Vegetation Index (NDVI and NDVI3g) data generated from the Advanced Very High Resolution Radiometer (AVHRR) in the deciduous broadleaf forest of northern China during 1986 to 2006, we analyzed spatial, temporal and spatiotemporal relationships and differences between ground-based growing season beginning (BGS) and NDVI (NDVI3g)-retrieved start of season (SOS and SOS3g), and compared effectiveness of NDVI and NDVI3g in monitoring BGS. Results show that the spatial series of SOS (SOS3g) correlates positively with the spatial series of BGS at all pixels in each year (P < 0.001). Meanwhile, the time series of SOS (SOS3g) correlates positively with the time series of BGS at more than 65% of all pixels during the study period (P < 0.05). Furthermore, when pooling SOS (SOS3g) time series and BGS time series from all pixels, a significant positive correlation (P < 0.001) was also detectable between the spatiotemporal series of SOS (SOS3g) and BGS. In addition, the spatial, temporal and spatiotemporal differences between SOS (SOS3g) and BGS are at acceptable levels overall. Generally speaking, SOS3g is more consistent and accurate than SOS in capturing BGS, which suggests that NDVI3g data might be more sensitive than NDVI data in monitoring vegetation leaf unfolding. Full article